Google H-Index: 72
US Permanent Resident since 1993
EDUCATION
Degrees:
Ph.D. in Management ScienceandComputer System, University of Kansas, 1991.
B.S. in Mathematics, Southwest Petroleum Institute, Sichuan, China, 1982.
Graduate Certificate:
M.B.A. National Center for Industrial Science and Technology Management
Development (co-sponsored by USA and China), Dalian University of Science and Technology, China, 1983.
PH.D. DISSERTATION
“Optimal Linear Production Systems: Models, Algorithms, and Computer Support Systems,” defended in August,1991 at the School of Business, University of Kansas. Advisor: Po-lung Yu
AWARDS AND HONORS
Member of National Data Expert Advisory Committee, China, December 2024.
ElectedFellow, Web Intelligence Academy (WIA), Venice, Italy, October 2023.
Recipient of Richard Price Award in Data Science, the Tenth International Conference on Information Technology and Quantitative Management (ITQM 2023), Oxford, UK, August 2023.
ElectedFellow, the Chinese Academy of Management (CAM), China, August 2023.
ElectedFellow, the International Academy of Information Technology and Quantitative Management (IAITQM), USA, December 2022
Elected Fellow,the Asia-Pacific Artificial Intelligence Association (AAIA), Hong Kong, June 2022.
Co-Recipient of Best Paper Award at the 20th IEEE/WIC/ ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT 2021), Melbourne, Australia, December 14-17, 2021.
Recipient of Cheng Siwei Global Prize, Cheng Siwei Foundation, Beijing, China, December 11, 2021.
Recipient of AI Gold Swallow Special Contribution Award, Artificial Intelligence Committee, China Electronic Chamber of Commerce, Hengyang, Hunan, China, October 10, 2021.
Co-Recipient of Best Paper Award at the Eighth International Conference on Information Technology and Quantitative Management (ITQM 2020-2021), Chengdu, China, July 9-11, 2021.
Recipient of 2018 WIC Outstanding Research Contribution Award, IEEE/WIC/ACM International Conference on Web Intelligence 2018 (WI'18), Santiago, Chile, December 3-6, 2018.
2018 Highly Cited Researches by Clarivate Analytics-Web of Sciences, November 2018.
Co-Recipient of 2016 Herbert Simon Award for Outstanding Contribution in Information Technology and Decision Making, the 5th International Conference on Information Technology and Quantitative Management, New Delhi, India, December 2017.
2017 Highly Cited Researchers by Clarivate Analytics-Web of Sciences, November 2017.
Academician,the International Eurasian Academy of Sciences, April 2017.
State Counselor (Scientific Advisor in Big Data) of the State Council of People’s Republic of China, invited and appointed by Chinese Premier Li Keqiang, June 2016.
Co-Recipient of Pattern Recognition Best Paper Award, the 23rd International Conference on Pattern Recognition, Cancun, Mexico, December 2016.
Application Contribution Award in System Science and System Engineering, The 19th China's National Conference of System Engineering, Beijing, October 2016.
2016 Highly Cited Researchers by Thompson and Reuters-Web of Sciences, September 2016.
The First Rank of Research Award by the Ministry of Education of China, January 2016.
Elected Fellow,the World Academy of Sciences for Advancement of Science, Vienna, Austria, November 2015.
Doctor Honoris Causa of Agora University, Romania, May 2014.
The First Rank of Research Award by the Ministry of Education of China, January 2012.
Adjunct Science Fellow, the Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia, March 2012.
Recipient of Best Paper Award at the Workshop of Computational Finance and Business Intelligence, the Eleventh International Conference on Computational Science, Singapore, June 1-June 3, 2011.
Recipient of Best Paper Award at the Workshop of Computational Finance and Business Intelligence, the Tenth International Conference on Computational Science, Amsterdam, Netherlands, May 31-June 2, 2010.
Recipient of Fudan Prize of Distinguished Contribution in Management, Fudan Premium Fund of Management, China, November 1, 2009.
Recipient of Georg Cantor Awardby InternationalSociety on Multiple Criteria Decision Making, June 24, 2009.
Recipient of Best ConferenceOrganization Award, at the twentieth International Conference on Multiple Criteria Decision Making, Chengdu, China, June 21-25, 2009.
Recipient of Best Paper Award at the Workshop of Computational Finance and Business Intelligence, the Ninth International Conference on Computational Science, Baton Rouge, Louisiana, USA, May 25-27, 2009.
Recipient of Best Paper Award at the Workshop of Computational Finance and Business Intelligence, the Eighth International Conference on Computational Science, Krakow, Poland, June 22-25, 2008.
Recipient of Best Service Award at the Seventh International Conference on Computational Science, Beijing, May 27-30, 2007.
Recipient of Best Paper Award at the Forth International Conference on Active Media Technology, Brisbane, Australia, July 7-9, 2006.
Member of Overseas Assessor for Chinese Academy of Sciences, May 2000.
Distinguished Visiting Speaker-2000, School of Business, University of Kansas, April 2000.
Recipient of University Award for Distinguished Research or Creative Activity,
University of Nebraska at Omaha, 1999.
Speaker of Distinguished Visitors Program (DVP) for 1997-2000, IEEE ComputerSociety.
First Recipient of Alumni Outstanding Teacher in Information Science andTechnology, University of Nebraska at Omaha, 1997.
Recipient of Best Theoretical Paper Award at The First International Conferenceon Operations and Quantitative Management, Jaipur, India, Jan. 5-8, 1997.
A University Research Fellow of 1994-1996, University Committee onResearch, University of Nebraska at Omaha.
First Recipient of The Dean's Citation in Recognition of Excellence inResearch, College of Business Administration, University of Nebraska at Omaha, 1993.
Ph.D. Dissertation Honors, School of Business, University of Kansas, Aug. 1991.
A member of Beta Gamma Sigma, the Honor Society for Collegiate Schools of Business, University of Kansas Chapter, May 1991.
Second National Prize of Scientific Technology Achievement by PetroleumIndustry Ministry of China for research on "Expert Systems for Petroleum Reservoir Engineering," 1983.
Annual Award of Excellent Student from Southwest Petroleum Institute,Sichuan, China, 1979-1982.
WORK EXPERIENCE
March 2018- Present: University Chair Professor, University of Chinese Academy of Sciences.
January 2005- February 2018: Distinguished Professor, University of Chinese Academy of Sciences.
August 2014- Present: Director, Key Lab of Big Data Mining and Knowledge Management, Chinese Academy of Sciences.
August 2004- Present: Director, Chinese Academy of Sciences Research Center on Fictitious Economy & Data Science.
September 2013-September 2014: Visiting Professor,College of Business, Korea Advanced Institute of Science and Technology, Seoul, Korea.
August 1999 - December 2004: the Charles W. and Margre H. Durham Distinguished Professor of Information Technology, College of Information Science and Technology, University of Nebraska at Omaha, USA.
January 2000 - March 2004: Professor (courtesy appointment) at Dept. of Marketing/Management, College of Business Administration, University of Nebraska at Omaha.
July 1996 - July 1999: Associate Professor with Tenure at Dept. of Information Systems and
Quantitative Analysis, College of Information Science and Technology, University of Nebraska at Omaha.
Aug. 1991 - July 1996: Assistant Professor and Associate Professorwith Tenure at Dept. of
Information Systems and Quantitative Analysis, College of Business Administration, University of Nebraska at Omaha.
December 1994 – December 2004: Graduate Faculty Fellow of Whole University of Nebraska System.
September2002-August 2005: EMBA Professor at Xi’an Jiaotong University, China.
November 2001 – October 2004: Honorary and EMBA Professor at Chinese University of Electronic Sciences, China.
November 1999 – May 2004: Honorary Professor at East China Normal University, China.
July 1998 – May 2000: Honorary Professor at Chongqing University of Posts andTelecommunications, China.
Jan. 1988 - July 1991: Instructor, School of Business, University of Kansas.
INDUSTRIAL PROJECTS
Credit Scoring and Prediction Systems (People’s Bank of China, i.e, China’s Central Bank)
Migration of VIP Internet Customers (Netease Co, China)
Fraud Management (China’s National Auditing Bureau)
Financial Risk Management (Chinese Industrial and Commercial Bank)
Currency Exchange Analysis (People’s Bank of China)
Petroleum Drilling and Exploration (BHP Billion, Co, Australia)
CONSULTING EXPERIENCE
May 2005-present: Industrial and Commercial Bank of China., Ltd., China
August 2002: Consulting the China National Offshore Oil Co., Ltd., China
August 2002: Consulting the China Unionpay Co., Ltd., China
August 2001- 2015: Consulting the Shanghai Credit Information Service Co., Ltd., China
July 2001- Present: Consulting CCID, Co., Ltd., China
May 2001- Present: Data Warehousing Project of China Construction Bank, China
February 1998- 2004: First Data Corporation, Omaha, USA
Summer 2001: First National Bank for Data Mining Projects, Omaha, USA
Fall 2000: Ameritrade Holding Corporation (Charls Schwab & Co.), USA
Fall 1998: Mutual of Omaha, Co. for building its Data Warehouse, USA
Fall 1995: Kiewit Construction Group Inc., Omaha, USA.
1993-1994: Build IS for Omaha Public Power District, Co., Omaha, USA
CURRENT RESEARCH INTERESTS
Methodological Areas:
Optimization Modeling
Multiple Criteria Decision Making
Multiple Criteria Multiple Mathematical Programming
Nonlinear Analysis
Fuzzy Sets and Systems
Functional Areas:
Artificial Intelligence with Business Applications
Big Data Mining and Analytics
Information Management
Intelligent Knowledge Management
Decision Support Systems
Bioinformatics
Aggregate Production Planning and Scheduling
Capital Budgeting
Transfer Pricing
Petroleum Engineering Management
Social Welfare and Capital Taxation
Agricultural Policy Making
COURSES TAUGHT
Graduate Programs:
Graduate Algorithms for Big Data and AI (UCAS)
AI and Big Data Analytics (UCAS)
Data Mining and Business Analytics (UCAS)
Multivariate Statistical Analysis (UCAS)
Doctoral Research Methods (CIST 9090)
Business Analytics (ISQA 8016)
Data Warehousing: Theory and Practice (ISQA 8700)
Information Systems Development (ISQA 8040)
Production and Operations Management and Business Calculus (BSAD 8170)
Business Quantitative Analysis (BSAD 8000)
Applied Quantitative Analysis (BSAD 8040)
Statistics for Business (BSAD 8120)
Undergraduate Programs:
Business Intelligence (ISQA 4010)
Multiple Criteria Decision Making (ISQA 4000, University Honors Program)
Data Warehousing and Data Mining (ISQA 4890)
Organizations, Applications and Technology (CIST 2100)
Production and Operations Management (ISQA 3500)
Principles of Business Statistics (ISQA 2130)
Intermediate Business Statistics (ISQA 3140)
Operations Research (ISQA 3150)
Intermediate Operations Research (ISQA 3250)
AWARDED GRANTS AND CONTRACTS
“Research on the Decision Behavior and Collaborative Management of Human-Machine System”,$304,347, by National Science Foundation of China, Key Project, #72231010, 2023-2027.
“Research on Construction of New Generation Business Intelligence System Based on Big Data Fusion”,$366,197, by National Science Foundation of China, Key Project, #71932008, 2020-2024.
“Non-structured Data Analysis Methods and Key Technologies for Management Decision Making”,$412.698, by National Science Foundation of China, Key Project, #91546201, 2016-2020.
“Innovative Research on Management Decision Making under Big Data Environment”,$352,365, by National Science Foundation of China, Key Project, #71331005, 2014-2018.
“Recommendation System Research”,$55,193, by Nebraska Furniture Market - a unit of Berkshire Hathaway Investment Co., Omaha, Nebraska 2016-2017.
“Business Intelligence Methods Based on Optimization Data Mining with Applications of Financial and Banking Management”,$380,952, by National Science Foundation of China, #71110107026, 2012-2016.
“Data Mining and Business Intelligence in Internet Advertisements”, $112,000, by Sojern, Inc, 2012-2013.
“Data Science-based Fictitious Economy and Environmental Policy Research: An Overseas Collaboration Group”,$735,294, by Chinese Academy of Sciences, 2010-2012.
“Creating Knowledge for Business Intelligence: Strengthening the Long-Term Partnership with Nebraska Furniture Mart”, $50,000, by Nebraska EPSCoR, 2009-2010.
“Research on Operational Structure of Sovereign WealthFunds”, $17,910, by National Science Foundation of China, Special Project, #09110421A, 2009.
“Data Mining for Petroleum Exploration-Phase II”,$300,000, by BHP Billiton Co., Australia, 2008-2013.
“The attributes Structure and Measurements in the Process of Building Trust-worth Software”, $100,000, by National Science Foundation of China, Key Project, #73662243, 2008-2010.
“Revolving Charge Accounts Receivable Retrospective Analysis”,$64,959, by Nebraska Furniture Market - a unit of Berkshire Hathaway Investment Co., Omaha, Nebraska 2008-2009.
“Data Mining and Intelligent Knowledge Management: Theory and Applications”,$1,423,077, by National Science Foundation of China, Innovative Grant，#70621001, #70921061, 2007-2012.
“Data Mining and Optimization”,$150,000, by National Science Foundation of China, Key Project，#70531040, 2006-2008.
“Data Mining for Petroleum Exploration-Phase I”,$54,500, by BHP Billiton Co., Australia, 2005-2007.
“Multiple Criteria Non-linear based Data Mining Methods and Applications”,$25,000, by National Science Foundation of China, #70472074, 2005-2007.
“Bio-informatics Study in the Process and Changes of Antigen and Antibody”, (with Z. Cao et al.) $316,000, by 973 Project, Chinese Department of Science and Technology, #2004CB720103, 2005-2009.
“Proactive and Predictive Information Assurance for Next Generation Systems (P2INGS)”,
(with J. Huff, Z. Chen and Q. Zhu) $800,000, US Air Force Research Laboratory, Contract # F30602-03-C-0247, October 2003-April 2005.
“Data Mining and Data Warehousing: Theory and Applications in Financial Fields”, $158,536 (1.3 million Chinese Yuan) by Chinese Department of Science and Technology, #01C26225120981, 2002-2004.
“Data Mining Laboratory”, (with Zhengxin Chen and Steven Stock) $50,000 by University ofNebraska Foundation, 2002.
“Data Mining Modeling for Financial Market”, $48,780 (400,000 Chinese Yuan) by Chinese Academy of Sciences, 2001-2005.
“Data Mining in Bank Loan Risk Management”, $73,170 (600,000 Chinese Yuan) by National Science Foundation of China, #70028101, 2001-2003.
“Data Mining in Chinese Insurance Marketing Analysis”, $7,744 by K.C. Wong Education Foundation, Chinese Academy of Sciences, 2001 and 2003.
“Use of Cutting-edge Information Technology to Infrastructure Management”, (with I. Bogardi) $25,000 by Peter Kiewit Institute, Omaha World-Herald Grants, 1999-2000.
“Evaluation of Public Key Infrastructure in Information Security: A Multiple CriteriaApproach,” $7,110 by College of Information Science and Technology, University of Nebraska at Omaha for summer research fellowship, 2000.
“Educating the Next Generation of Information Specialists”, (with Doris Lidtke) $265,680 by National Science Foundation, DUE-9796243, 1999.
“Multiple Criteria Decision Making in Credit Card Portfolio Management”, $41,873 by First Data Corporation, Omaha, 1998.
“Information Decision Making in Commercial Integrated Automation”,$10,500 by China Bridges International (North America) and Chinese National Science Foundation, 1998-2000.
“Information Decision Making”,$6,000 by University Committee on Research, University of Nebraska at Omaha for Summer Research Fellowship, 1997.
“A Theory of Optimal Production System Designs and Applications”,$6,200 by University Committee on Research, University of Nebraska at Omaha for Research Fellowship of 1994-1996.
“Production Manager Training Program”,$3,000,000 by China’s National Petroleum Corporation and University of Nebraska at Omaha, 1993-1995.
“An Aggregate Production Planning Model with Multiple Criteria and Multiple Resource Availability Levels”,$5,000 by University Committee on Research, University of Nebraska at Omaha for summer research fellowship, 1993.
“Optimal Linear Production Systems and Optimal Contingency Plan: Contribution Adjustment Analysis”,$5,000 by University Committee on Research, University of Nebraska at Omaha for summer research fellowship, 1992.
SUPERVISIONS TO GRADUATE STUDENTS
Doctoral Dissertation (2002- present):
1. Zhenglin Liu, “Evaluations and Decisions on Investment of Venture Capitals”, graduated at Chinese Academy of Sciences, October 2002 (Co-Advisor).
2. Jainping Li, “Data Mining Techniques and Its Applications in Financial Market”, graduated at Chinese Academy of Sciences, May 2004 (Co-Advisor).
3. Jing He, “Data Mining Frameworks of Output-Input Analyses in Large-scale Economy Forecasting”, graduated at Chinese Academy of Science, May 2005 (Co-Advisor).
4. Gang Kou, “Multi-Class Multi-Criteria Mathematical Programming and its Applications in Large Scale Data Mining Problems,” graduated at University of Nebraska at Omaha, November 2006 (Co-Advisor).
5. Yi Peng, “A Descriptive Framework for the Field of Data Mining and Knowledge Discovery,” graduated at University of Nebraska at Omaha, January 2007 (Co-Advisor).
6. Anhua Li, “Research on Consumption Debit Problems Based on Data Technology”, graduated at Chinese Academy of Sciences, May 2007 (Co-Advisor).
7. Xingsen Li, “Framework Structure of Intelligent Knowledge Management”, graduated at Chinese Academy of Sciences, May 2008
8. Rong Liu, “Sampling and Succinct Matrix Approximation”, graduated at Chinese Academy of Sciences, May 2008
9. Peng Zhang, “Mining Concept Drifting Data Streams”, graduated at Chinese Academy of Sciences, May 2009 (Advisor).
10. Zhiwang Zhang, “Research on Uncertain Multiple Criteria Programming Models and Algorithms for Classification”, graduated at Chinese Academy of Sciences, May 2009 (Advisor).
11. Dongling Zhang, “Research on Knowledge-incorporated Optimization based Classification and Regression Problem”, graduated at Chinese Academy of Sciences, May 2009 (Advisor).
12. Meihong Zhu, “Research on the Analysis and Improvement of the Performance of Multiple Criteria Linear Programming Classification Method”, graduated at Chinese Academy of Sciences, May 2009 (Advisor).
13. Nian Yan, “Non-Additive Measure of Optimization-Based Data Mining Technologies and Applications”, graduated at University of Nebraska at Omaha, May 2010 (Co-Advisor).
14. Yuejin Zhang, “Research on Intelligent Knowledge Discovery and Management Based on Association Rule Mining and Classification”, graduated at Chinese Academy of Sciences, May 2010 (Advisor).
15. Ruoyng Chen, “The Study Prediction ofProteinsInteraction Hot Spots and Protein-protein Interface Based on Data Mining”, graduated at Chinese Academy of Sciences, May 2011
16. GuangliNie, “Classification Based Intelligent Knowledge Discovery and its Application to Risk Management”, graduated at Chinese Academy of Sciences, May 2011
17. Zhongbin Ouyang, “Research n Data Mining in Petroleum Engineering Management and Its Application”, graduated at Chinese Academy of Sciences, October 2011
18. Yinhua Li, “Settlement Risk Management of Stock Index Futures”, graduated at Chinese Academy of Sciences, November 2012
19. Warawut Suphamitmongkol, “Multi-Criteria Optimization Data Mining in Agricultural Quality Control Based on Near Infrared Spectroscopy,” graduated at Chinese Academy of Sciences, August 2013
20. Bo Wang, “The Study f Error Correction in Classification Based on Multiple Criteria andMultiple-Constraint Levels Linear Programming,” graduated at Chinese Academy of Sciences, November 2013
21. Xi Zhao, “ASeries of Data Mining Methods for Big Data Era”, graduated at Chinese Academy of Sciences, August 2014
22. Yibing Chen, “Systemic Risk Management and Deposit Insurance Pricing of Chinese Commercial Banks”, graduated at Chinese Academy of Sciences, May 2015
23. Feng Liu, “World Search Engine IQ Test Based n The Internet IQ Evaluation Algorithms”, graduated at Chinese Academy of Sciences, November 2015
24. Zuofang Yang, “E-retail Delivery Efficiency and Supplier Performance Evaluationin China”, graduated at Chinese Academy of Sciences, November 2015
25. Wei Deng, “Hybrid and Dynamic Recommender Models for Consumer Decision Making and Marketing”, graduated at University of Nebraska at Omaha, November 2016 (Co-
26. Hosseini Bamakan Seyed Mojtaba, “Intelligent Intrusion Detection Research Based on Kernel Methods", graduated at Chinese Academy of Sciences, February 2017
27. Huadong Wang, “Large-scale Nonparallel Support Vector Ordinal Regression", graduated at Chinese Academy of Sciences, May 2017
28. Fan Meng, “Large Scale Image Semantic Label Learning", graduated at Chinese Academy of Sciences, May 2017
29. Tingxiang Bao, “Research on Information Safeguard and Personnel Training in Military", graduated at Chinese Academy of Sciences, November 2017
30. Zhongxing Wang, “Research on the interest rate transmission of monetary policy based on network analysis of China bond market", graduated at Chinese Academy of Sciences, May 2018
31. Jianyu Miao, “Joint Sparsity Regularization and its Applications in Feature Selection”, graduated at Chinese Academy of Sciences, May 2018
32. Zhensong Chen, “Research on the Problem of Learning with Label Proportions and Its Applications in Health big data Mining”, graduated at Chinese Academy of Sciences, May 2018
33. Limemh Cui, “On Learning from Heterogeneous Data”, graduated at Chinese Academy of Sciences, May 2018
34. Peijia Li, “Ordinal Regression Method and its Application Research”, graduated at Chinese Academy of Sciences, May 2018
35. Jiabin Liu, “Research on Several Issues for Learning from Label Proportion”, graduated at Chinese Academy of Sciences, May 2019
36. Minglong Lei, “Research on Network Embedding Methods”, graduated at Chinese Academy of Sciences, May 2019
37. Yeran Tang, “Research on Investor Sentiment in China’s Stock Market: Measurement, Impact and Formation Mechanism”, graduated at the Chinese Academy of Sciences, May 2019
38. Baio Li, “Research on Image Resolution-Based Management Decision and Application”, graduated at the Chinese Academy of Sciences, May 2020 (Advisor).
39. Yunlong Mi, “Concept-cognitive Computing Theory and Models”, graduated at the Chinese Academy of Sciences, May 2020 (Advisor).
40. Yuanchun Zheng, “Research on Text Sentiment Analysis based on Multi-Sense WordEmbedding and Attention Networks”, graduated at the Chinese Academy of Sciences, May 2020 (Advisor).
41. Wei Dai, “Research on Dynamic Process Analysis and Its Application for Ultra High Frequency Trading Data in China Stock Market”, graduated at the Chinese Academy of Sciences, May 2021
42. Wenlu An, “Research on the applications of intelligent prosecution based on text big data mining”, graduated at the Chinese Academy of Sciences, May 2021
43. Zongyou Wu, “Research on Medical and Health Big Data Mining and Applications”, graduated at the Chinese Academy of Sciences, October 2021
44. Yang Xiao, “Relation Extraction Based on Graph Representation Learning”, graduated at the Chinese Academy of Sciences,April 2021
45. Jie Yang, “Unsupervised Visual Anomaly Detection and Recognition Based on Deep Learning”, graduated at the Chinese Academy of Sciences,April 2021
46. Bo Li, “Financial market simulation and financial forecasting based on machine learning”, graduated at the Chinese Academy of Sciences,April 2021
47. Xiaodong Xue, “Research on data-driven artificial intelligence models and methods of fault detection in nuclear power plants”, graduated at the Chinese Academy of Sciences,April 2022
48. Pei Quan, “Research on Neural Network based Graph Representation learning Methods and Applications”, graduated at the Chinese Academy of Sciences,April 2022
49. Guangfeng Qiang, “Research on Monitoring the Effectiveness of the National ‘Double Reduction’ Education Policy”, graduated at the Chinese Academy of Sciences,April 2023
50. Zhanbin Zhang, “Research on target evaluation and control strategy of Low-altitude UVA”, graduated at the Chinese Academy of Sciences,October 2023
51. Mengyu Shang, “Research on Deep Learning based intelligent Image Composition Methods and Applications”, graduated at the Chinese Academy of Sciences,October 2023
52. Yi Qu, “Research on models and applications of credit risk prediction based on graph neural networks”, graduated at the Chinese Academy of Sciences,November 2023
53. Anda Tang, “Research on deep learning lightweight based on sparse optimization”, graduated at the Chinese Academy of Sciences, April 2023
54. Linzi Zhang, “Research on Data-Driven Predictive Maintenance Approaches and Applications in Cmputing Power Networks”, graduated at the Chinese Academy of Sciences, April 2024
55. Yunong Wang, “Research on Stock Price Prediction and Portfolio Management Based on Asset Price Co-m, graduated at the Chinese Academy of Sciences, May 2025
56. Jiayu Xue, “Reference-Based Image Super-Resolution: Methodologies and Technical Advancements”, graduated at the Chinese Academy of Sciences, May 2025
57. Lei Zheng, “Graph Representation Learning Based on Optimal Transport and Its Lightspeed Computation”, graduated at the Chinese Academy of Sciences, May 2025
Master Degree Thesis (2000 – present):
1. Wei Fan, “An Integer Solution for Linear Programming with Multi-Criteria and Multi-Constraint Level: A Branch-and-Bound Algorithm”, graduated in Computer Science, at University of Nebraska at Omaha, November 2000 (Advisor).
2. Shawn Halls, “Customer Acceptance Is the Key to Success of Electronic Bill Presentment and Payment”, graduated in Management Information Systems, at University of Nebraska at Omaha, June 2002 (Advisor).
3. Lei Wang, “Comparison Study 2Integer Linear Programming Approaches”, graduated in Computer Science, at University of Nebraska at Omaha, June 2002 (Advisor).
4. Yi Peng, “Data Mining in Credit Card Portfolio Management: Classifications for Cardholders’ Behavior”, graduated in Management Information Systems, at University of Nebraska at Omaha, October 2002 (Advisor).
5. Jun Zhu, “Classification and Predication of Early Stage Neural Cell Dendritic Alternations Using Artificial Neural Networks”, graduated in Computer Science, at University of Nebraska at Omaha, June 2003 (Co-Advisor).
6. Gang Kou, “Linear Classification Algorithms of Data Mining in Linux and Its Applications”, graduated in Computer Science, at University of Nebraska at Omaha, August 2003 (Co-Advisor).
7. Wei Zhuang, “Studies on Classification Methods in Data Mining via Two Real-life Databases”, graduated in Management Information Systems, at University of Nebraska at Omaha, December 2003 (Advisor).
8. Menjun Wang, “Statistical Design and Analysis in Neural Dendritic and Synaptic Damage Resulting From HIV-1-Associated Dementia”, graduated in Computer Science, at University of Nebraska at Omaha, April 2004 (Co-Advisor).
9. Nian Yan, “Classification using Neural Networks Ensemble with Feature Selection”, graduated in Computer Science, at University of Nebraska at Omaha, July 2004 (Co-Advisor).
10. Jiaxiong Pi, “Similarity and Cluster Analysis of Time Series Data Using R*-Trees”, graduated in Computer Science, at University of Nebraska at Omaha, August 2005 (Co-Advisor).
11. Yanming Li, “Study on the Application of Customer Knowledge Management in Real Estate Enterprise”,graduated in management science and engineering, at Chinese Academy of Sciences, April 2006
12. Zhimin Chen, “Research on the Construction of Alert Indicator System for EastTurkistan IslamicMovement”, graduated in Management Science and Engineering, at Chinese Academy of Sciences, May 2006
13. Xinyang Zhang, “Comparison two Kernel-based Learning Algorithms for Prediction the Distance Range between Antibody Interface Residues and Antigen Surface”, graduated in Software Engineering, at the Chinese Academy of Sciences, November 2006
14. Wei Yin, “Optimization Based Classification Algorithms and Application”,graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2007 (Advisor).
15. Jing Wang, “Research on Utility Mining and Its Applications”, graduated in Computer Science, at the Chinese Academy of Sciences, May 2007 (Advisor).
16. Jingdan Liu, “The Application Data Miningin D J FinanceInformation”, graduated in MBA, at the Chinese Academy of Sciences, May 2007 (Advisor).
17. Lin Zhou, “Exploration of Classification and Measurement System of Intelligent Knowledge”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2008
18. Jie Wei, “Objective Measurements of Intelligent Knowledge”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2008
19. Yaohui Chai, “Multi-Classification by Multiple Criteria Linear Programming Models with KPCA”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2008
20. Zhan Zhang, “Locality PreservingProjection Clustering”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2008
21. Yuehua Zhang, “A Source Code Mining Based TrustworthySoftware Attribute Research”,graduated in Computing Engineering, at the Chinese Academy of Sciences, May 2010 (Advisor).
22. Ying Wang, “The Research on Credit Risk Management of Commercial Banks in China”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2010 (Advisor).
23. Xiuxiang Zhao, “Research on Data Mining Approaches to Software Defects”, graduated in Computing Engineering, at the Chinese Academy of Sciences, May 2010 (Advisor).
24. Rui Wang, “Fund Performance Evaluation Based on Data Mining Classification Algorithm”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2011
25. Dwayne Belongia, “Predicting the Credibility of Market Basket Analysis by using Error Estimating Techniques: Application of Micro Ingredient Manufacturing Sales Data ”, graduated in Management Information Systems, at University of Nebraska at Omaha, December 2011
26. Li Fan, “Efficient Report Generation by UsingETL in Large-scale Databases”, graduated in Computer Science, at University of Nebraska at Omaha, January 2012 (Co-
27. Jing Chu, “Data Mining based on Non-additive Measure and Non-Linear Integrals”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2012
28. GuodongHuang, “Forecast Shanghai Composite Index with Data Mining”, graduated in MBA, at the Chinese Academy of Sciences, May 2013
29. Fengjuan Gao, “Foreign Exchange Risk Exposure Management of Commercial Banks Using Data Mining”, graduated in MBA, at the Chinese Academy of Sciences, May 2013
30. Lei Yang, “Graph-based Semi Supervised Learning Algorithm and Its Application in Imaging Processing”, graduated in Mathematics, at the Chinese Academy of Sciences, May 2013
31. Ye Wang, “Research on Financial CIndex Establishment Method and Its Multi-country Empirical Cgraduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2013
32. Fang Wang, “Advertisement Clicking Prediction by using Multiple Criteria Mathematical Algorithms”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2014
33. Chengcheng Liu, “The Study of Data Mining and Its Application in The Medical Management,” graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2014
34. Jing Tang, “Financial Innovation in the Chinese Personal Credit Industry: learning from the American experiences,” graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2017 (Co-
35. Fuhai Ma, “Research on the Classification of Commercial Banks’ Fund Clients,” graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2017
36. Wei Li, “Sentiment Lexicon and Neural Network Based Sentiment Analysis on Chinese Tourism Reviews”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2018
37. Yue Zhang, “An Empirical Study on Credit Risk Measurement Based on Financial Indicators of Industrial Machinery Manufacturing Enterprises”, graduated in MBA, at the Chinese Academy of Sciences, May 2018
38. Zhen Pang, “Prediction and Application Research of Hospitalization days based on medical data mining”, graduated in MBA, at the Chinese Academy of Sciences, May 2018
39. Jinxing Song, “Research on strategic development and strategic implementation control of military industrial enterprises under the background of military and civilian integration -Case study of aerospace institute A”, graduated in MBA, at the Chinese Academy of Sciences, May 2018
40. Xiao Tang, “A Research on Business Model Innovation of A Development Bank Based on Big Data”, graduated in MBA, at the Chinese Academy of Sciences, May 2018
41. Luyao Zhu,“Sentiment Analysis and Application on Finance Social Media User Reviews”, graduated in Management Science and Engineering, at the Chinese Academy of Sciences, May 2019
42. Shiqing Zhang, “Research on Customs Security Data Analysis and Decision Support”, graduated in MBA, at the Chinese Academy of Sciences, May 2019
43. Ningning Song, “An Empirical Study about the Evaluation System of 4S Store of New Energy Vehicles’ operational capability”, graduated in MBA, at the Chinese Academy of Sciences, May 2019
44. Xin Li, “Research on Self-research and Outsourcing Decision-making of Informatization Project of Gansu Civil Aviation Airport Group”, graduated in MBA, at the Chinese Academy of Sciences, May 2019
45. Chong Chen, “Research about Business Model Innovation of New Energy Automobile Manufacturers in Post-subsidy Era”, graduated in MBA, at the Chinese Academy of Sciences, May 2019
46. Zongping Zhao, “Application Research of Machine Learning in Community Life Precision Service：The case of A company”, graduated in MBA, at the Chinese Academy of Sciences, May 2019
47. Xinyue Ren, “Mining and Analysis of China’s County Economic Development Patterns based on Power Big Data”, graduated at the Chinese Academy of Sciences,April 2021
48. Shihang Pang, “Analysis of Dynamic Spillover Effects and Systemic Risks in the World Stock MARKET”, graduated at the Chinese Academy of Sciences,July 2020
49. Yuan An, “Better to ear All Parties: Research on the impact of Homophily in Online Financial DIscussion”, graduated at the Chinese Academy of Sciences, April 2022
50. Xueqing Geng, “Dynamic Structure of Exchange Rate Volatility of Currencies among Belt and Road Region Based on Network Analysis”, graduated at the Chinese Academy of Sciences, April 2021
51. Chunrong Qiao, “Exchange Rate Pass-through to Export Prices in RMB: Based on Inter-provincial Panel Data”, graduated at the Chinese Academy of Sciences, April 2021
52. Huanhuan Xi, “Research on Marketing Strategy of NP Hebei Company”, graduated at the Chinese Academy of Sciences, April 2021
53. Lu Wang, “Analysis on the Growth Characteristics of Re-purchase based on the Private Domain Traffic of E-commerce APP”, graduated at the Chinese Academy of Sciences, April 2021
54. Kai Zhang, “Research on Financing Scheme of small and micro enterprises based on big data and blockchain Technology”, graduated at the Chinese Academy of Sciences, April 2021
55. Yixin Yao, “Research on the relationship between the sales of partial equity public funds and the fluctuation of CSI 300 index”, graduated at the Chinese Academy of Sciences, April 2021
56. Xiaoqi Gao, “Cardiovascular disease screening and health management based on artificial intelligence”, graduated at the Chinese Academy of Sciences, April 2022
57. Yuanying Zhang, “Research on Federated Learning Optimization Algorithm Based on Sparse Regularization”, graduated at the Chinese Academy of Sciences, April 2023
58. Yao Tang, “Analysis on the impact of venture capital intervention on enterprise innovation investment”, graduated at the Chinese Academy of Sciences, April 2023
59. Jiulin Tang, “Analyze the Factors Affecting Systemic Banking Crises and Predict the probabilities”, graduated at the Chinese Academy of Sciences, April 2023
60. Jiaxin Tian, “Research on the impact of green finance on the high-quality development of provincial economy”, graduated at the Chinese Academy of Sciences, April 2023
61. Hong Sheng, “The mechanism of executive education in sci&tech training in business schools boosting the transformation of scientific and technological achievements in universities - A Case Study of W Business School”, graduated at the Chinese Academy of Sciences, April 2023
62. Nan Gao, “Market Prediction of Domestic X86 Architecture CPU Chips”, graduated at the Chinese Academy of Sciences, April 2024
63. Jiaxin Cui, “Research on Named Entity Recognition in Electronic Medical Records Based on Deep Learning - Digital Medicine and Management”, graduated at the Chinese Academy of Sciences, April 2024
64. Shanwei Cao, “Climate Risks Impacts on Chinese Agricultural Futures Price Volatility”, graduated at the Chinese Academy of Sciences, April 2024
PROFESSIONAL SOCIETIES
President of Chinese Academy of Management (CAM)(2015-2025)
President of International Academy of Information Technology and Quantitative Management (IAITQM)(2012-Present)
The International Eurasian Academy of Sciences (IEAS), Academician
The World Academy of Sciences for Advancement of Science (TWAS), Elected Fellow
The American Association for the Advancement of Science (AAAS)
Senior Member of IEEE
The Institute for Operations Research and Management Sciences (INFORMS)
The Decision Sciences Institute (DSI)
International Society of Multiple Criteria Decision Making (MCDM)
PROFESSIONAL SERVICES
Founder and Editor-in-Chief:
http://www.worldscinet.com/ijitdm/ijitdm.shtml
Founder and Editor-in-Chief:
http://www.springer.com/business+%26+management/journal/40745
Editor-in-Chief (2007-2013):
Journal of Management Review (in Chinese)
Area Editor:
International Journal of Operations and Quantitative Management
Member of Editorial Review Board of
Human Systems Management
Information – International Inter-discipline Journal
International Journal of Business Intelligence and Data Mining
International Journal of Computers, Communications & Control (IJCCC)
International Journal of Data Mining, Modelling and Management
International Journal of Knowledge and Systems Science (IGI)
International Journal of Service Science
Journal of Computational Science
Technological and Economic Development of Economy
Web Intelligence and Agent Systems
Ad hoc Referee:
Management Science
Operations Research
IEEE Transactions on Systems, Man, and Cybernetics: Part C
Journal of Optimization Theory and Applications
Operations Research Letters
Computers and Operations Research
Decision Support Systems
International Journal of Approximate Reasoning
Annals of Operations Research
Omega: The International Journal of Management Science
IIE Transactions
SIAM Journal on Control and Optimization
International Journal of Production Economics
Mathematical and Computer Modelling
Engineering Economist
Computers and Industrial Engineering
International Transactions in Operational ResearchSystem Sciences
Review of Quantitative Finance and Accounting
Served as session chair, panel discussant, and organizing committee member in numerous national and international conferences
CHAIRMAN FOR INTERNATIONAL CONFERENCES
May 27-30, 2007, organized and co-chaired the 7th International Conference on Computational Science, Beijing, where more than 600 scholars have participated from 48 different countries.
Oct. 28-31, 2007, organized and co-chaired the 2007 IEEE International Conference on Data Mining (ICDM 2007), Omaha, NE, USA, where more than 350 scholars have participated from 47 different countries.
May 24-26, 2009, organized and co-chaired the International Conference on Linear Programming Algorithms and Extensions, Haikou, Hainan Island, China, where 30international leading scholars in the field were invited and have participated from 6 different countries and regions.
June 21-26, 2009, organized and co-chaired the 20th International Conference on Multiple Criteria Decision Making, Chengdu, China, where more than 250 scholars participate from 31 different countries and regions.
June 23-25, 2010, honorary chair of the 2nd International Conference on Software Engineering and Data Mining, Chengdu, China, where more than 150 scholars participate from 5 different countries and regions.
July 23-25, 2010, organized and co-chaired the 18th Annual Conference onPacific Basin Finance, Economics, Accounting and Management, Beijing, China, where 250international leading scholars in the field were invited and have participated from 18 different countries and regions.
May 29-30, 2011, organized and co-chaired the Second International Symposium on Dataology& Data Science, Beijing, China, where 45international leading scholars in the field were invited and have participated from 7 different countries and regions.
June 3, 2012, organized and co-chaired the Inauguration Meeting of International Academy of Information Technology and Quantitative Management, Omaha, Nebraska, USA, where 50 international leading scholars in the field were invited and have participated from 13 different countries and regions.
June 4-June 6, 2012, organized and co-chairedthe Twelfth International Conference on Computational Science, Omaha, Nebraska, USA, where 320 international leading scholars in the field were invited and have participated from 33 different countries and regions.
May16-18, 2013, organized and co-chaired the First International Conference on Information Technology and Quantitative Management (ITQM 2013), Suzhou, China, where 250 international scholars in the field were invited and have participated from 20 different countries and regions.
June3-5, 2014, organized and co-chaired the Second International Conference on Information Technology and Quantitative Management (ITQM 2014), Moscow, Russia, where 200international scholars in the field were invited and have participated from 26 different countries and regions.
July 21-24, 2015, organized and co-chaired the Third International Conference on Information Technology and Quantitative Management (ITQM 2015), Rio, Brazil, where 250international scholars in the field were invited and have participated from 32 different countries and regions.
April 30-May 2, 2016, organized and co-chaired the First Sino-American Venture Capital Summit (SAVCS 2016), Omaha Nebraska, where120international investors and startups have participated from several countries and regions.
August 16-18, 2016, organized and co-chaired the Forth International Conference on Information Technology and Quantitative Management (ITQM 2016), Asan, Korea, where 20international scholars in the field were invited and have participated from 18 different countries and regions.
October 13-16, 2016, organized and co-chaired 2016 IEEE / WIC / ACM International Conferences, Omaha, Nebraska, USA.
May 5-7, 2017, organized and co-chaired the Second Sino-American Venture Capital Summit (SAVCS 2017), Omaha Nebraska, where420international investors and startups have participated from several countries and regions.
November 25, 2017, organized and co-chaired the Second Global Investment Conference (GIC 2017), Beijing, China, where1000international investors and startups have participated from several countries and regions.
December 8-10, 2017, organized and co-chaired the Third International Conference on Information Technology and Quantitative Management (ITQM 2017), New Delhi, India, where 200international scholars in the field were invited and have participated from 21 different countries and regions.
May 4-6, 2018, organized and co-chaired the Third Sino-American Venture Capital Summit (SAVCS 2018), Omaha Nebraska, where700international investors and startups have participated from several countries and regions.
June 6-9, 2018, organized and co-chaired the FifthInternational Conference on Data Science (ICDS 2018), Beijing, China, where 100international scholars in the field were invited and have participated from 7 different countries and regions.
June 11-13, 2018, organized and co-chairedthe Eighteenth International Conference on Computational Science (ICCS 2018), Wuxi, China, where 410 international leading scholars in the field were invited and have participated from 36 different countries and regions.
October20-21, 2018, organized and co-chaired the SixthInternational Conference on Information Technology and Quantitative Management (ITQM 2018), Omaha, USA, where 110 international scholars in the field were invited and have participated from 16 different countries and regions.
November 11, 2018, organized and co-chaired the Third Global Investment Conference (GIC 2018), Beijing, China, where500international investors and startups have participated from several countries and regions.
May 3, 2019 - May 5, 2019, Organizing the Forth Sino-American Venture Capital Summit (SAVCS 2019), Omaha, NE, where 250 international scholars and businessmen in the field were invited and have participated.
May 12, 2019 - May 13, 2019, organized and chaired 2019 The First Tianfu International Forum on Big Data and Digital Economy (TBDF 2019), Chengdu, China, where 550international scholars and businessmen in the field were invited and have participated from 8 different countries and regions.
May 15, 2019 - May 20, 2019, Organizing the Sixth International Conference on Data Science (ICDS 2019), Ningbo, China, where 150international scholars and businessmen in the field were invited and have participated.
November 3-6, 2019, organized and co-chaired the Seventh International Conference on Information Technology and Quantitative Management (ITQM 2019), Granada, Spain, where 230 international scholars in the field were invited and have participated from 18 different countries and regions.
May 1, 2020, Organizing the Fifth Sino-American Venture Capital Summit (SAVCS 2020), A Global Online Meeting by Zoom, where around 160,000 international scholars and businessmen in the field have participated via Baidu live broadcasting.
December 26, 2020-December 27, 2020, Organized the Seventh International Conference on Data Science, Chengdu, China, Conference (Online).
April 30, 2021, Organizing the Sixth Sino-American Venture Capital Summit (SAVCS 2021), A Global Online Meeting by Zoom, where around 300,000 international scholars and businessmen in the field have participated via Baidu live broadcasting.
July 9-11, 2021, organized and co-chaired the Eighth International Conference on Information Technology and Quantitative Management (ITQM 2020-2021), Chengdu, China, where 350 international scholars in the field were invited and have participated from 23 different countries and regions.
November 19-21, 2021, Organized the Eighth International Conference on Data Science, Nanjing, China, Conference (Online).
December 9-11, 2022, organized and co-chaired the Nineth International Conference on Information Technology and Quantitative Management (ITQM 2022), Beijing, China, where 260 international scholars in the field were invited and have participated from 28 different countries and regions.
December 20, 2022，organizing the Ninth International Conference on Data Science (ICDS 2022), Oxford, UK, where 100 international scholars and businessmen in the field were invited and have participated.
August 12-14, 2023, organized and co-chaired the Tenth International Conference on Information Technology and Quantitative Management (ITQM 2023), Oxford, UK, where 210 international scholars in the field were invited and have participated from 25 different countries and regions.
May 4-7，2023, organizing the Eighth Sino-American Venture Capital Summit (SAVCS 2023), Omaha Nebraska, where 100 international investors and startups have participated from several countries and regions.
August 23-25, 2024, organized and co-chaired the Eleventh International Conference on Information Technology and Quantitative Management (ITQM 2024), Bucharest, Romania, where almost 100 international scholars in the field were invited and have participated from 21 different countries and regions.
May 3，2024, organizing the Ninth Sino-American Venture Capital Summit (SAVCS 2024), Omaha Nebraska, where 200 international investors and startups have participated from several countries and regions.
December 7-8, 2024，organizing the Tenth International Conference on Data Science (ICDS 2024), Shenzhen, China, where 200 international scholars and businessmen in the field were invited and have participated.
August 15-17, 2025, organized and co-chaired the Twelfth International Conference on Information Technology and Quantitative Management (ITQM 2025), Newark, New Jersey, USA, where almost 100 international scholars in the field were invited and have participated from 20 different countries and regions.
May 2-3，2025, Organizing the Tenth Sino-American Venture Capital Summit (SAVCS 2025), Omaha Nebraska, where 200 international investors and startups have participated from several countries and regions.
CHAIRMAN FOR INTERNATIONAL WORKSHOPS
May 31-June 2, 2010, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Tenth International Conference on Computational Science, Amsterdam, Netherlands.
Aug. 31-Sept. 3, 2010, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2010 IEEE / WIC / ACM International Conferences, Toronto, Canada.
Dec. 14-17, 2010, organized and co-chaired the 2010 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'10), the 2010 IEEE International Conference on Data Mining, Sydney, Australia.
June 1-June 3, 2011, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Eleventh International Conference on Computational Science, Singapore.
Aug. 22-Aug. 27, 2011, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2011 IEEE / WIC / ACM International Conferences, Lyon, France.
Dec. 11-15, 2011, organized and co-chaired the 2011 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'11), the 2011 IEEE International Conference on Data Mining, Vancouver, Canada.
June 4-June 6, 2012, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Twelfth International Conference on Computational Science, Omaha, Nebraska, USA.
June 5-June 7, 2013, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Thirteenth International Conference on Computational Science, Barcelona, Spain.
Nov. 17-Nov. 20, 2013, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2013 IEEE / WIC / ACM International Conferences, Atlanta, USA.
Dec. 7-10, 2013, organized and co-chaired the 2013 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'13), the 2013 IEEE International Conference on Data Mining, Dallas, Texas.
June 10-June 12, 2014, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Fourteenth International Conference on Computational Science, Cairns, Australia.
Aug. 11-Aug. 14, 2014, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2014 IEEE / WIC / ACM International Conferences, Warsaw, Poland.
Dec. 14-17, 2014, organized and co-chaired the 2014 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'14), the 2014 IEEE International Conference on Data Mining, Shenzhen, China.
June 1-June 3, 2015, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Fifteenth International Conference on Computational Science, Iceland.
Nov.15-17, 2015, organized and co-chaired the 2015 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'15), the 2015 IEEE International Conference on Data Mining, Atlantic City, NJ, USA.
Dec. 6-9, 2015, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2015 IEEE / WIC / ACM International Conferences, Singapore.
June 6-8, 2016, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Sixteenth International Conference on Computational Science, San Diego, California, U.S.A.
October 13-16, 2016, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2016 IEEE / WIC / ACM International Conferences, Omaha, Nebraska, USA.
December 12-15, 2016, organized and co-chaired the 2016 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'16), the 2016 IEEE International Conference on Data Mining, Barcelona, Spain.
June 12-14, 2017, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Seventeenth International Conference on Computational Science, Zürich, Switzerland.
August 23-24, 2017, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2017 IEEE / WIC / ACM International Conferences, Leipzig, Germany.
November 18-21, 2017, organized and co-chaired the 2017 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'17), the 2017 IEEE International Conference on Data Mining, New Orleans, LA, USA.
June 11-13, 2018, organized and co-chaired the Workshop of Computational Finance and Business Intelligence, the Eighteenth International Conference on Computational Science (ICCS 2018), Wuxi, China.
November17-20, 2018, organized and co-chaired the 2018 Workshop on Optimization Based Methods for Emerging Data Mining Problems (OEDM'18), the 2018 IEEE International Conference on Data Mining, Singapore.
December 4-6, 2018, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI), 2018 IEEE / WIC / ACM International Conferences, Santiago, Chile.
June 12, 2019 - June 14, 2019, organized and co-chaired the Workshop of Computational Finance and Business Intelligence at the 19th International Conference on Computational Science, Portugal.
October 14, 2019 - October 17, 2019, organized and co-chaired the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI) at 2019 IEEE / WIC / ACM International Conferences, Greece.
November 8, 2019 - November 11, 2019, organized and co-chaired the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2019 IEEE International Conference on Data Mining, China.
November 17, 2020- November 20, 2020, organized the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2020 IEEE International Conference on Data Mining, Sorrento, Italy.
December 14, 2020 - December 17, 2020, organized the workshop on Optimization-based Data Mining and Web Intelligence (WI: ODMWI) at 2020 IEEE / WIC / ACM International Conferences, Australia (Online).
December 7-11, 2021, organized the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2021 IEEE International Conference on Data Mining, Auckland, New Zealand.
December 9-11, 2022, organized the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2022 IEEE International Conference on Data Mining, Beijing, China.
August 12-14, 2023, organized the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2023 IEEE International Conference on Data Mining, Oxford, UK.
August 23-25, 2024, organized the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2024 IEEE International Conference on Data Mining, Bucharest, Romania.
August 15-17, 2025, organized the workshop on Optimization Based Methods for Emerging Data Mining Problems at the 2025 IEEE International Conference on Data Mining, Newark, New Jersey, USA.
KEYNOTE/INVITED SPEECHES AT CONFERENCES
Multiple Criteria Decision Making and Data Mining, the 2007 IEEE/WIC/ACM International Conference on Web Intelligence (WI 2007), Nov. 1-2, 2007, Silicon Valley, USA
A Family of Optimization based Data Mining Methods, Apweb 2008, the 10th Asia Pacific Web Conference, April 26-28, 2008, Shenyang, China
Credit Scoring System: Multiple Criteria Programming- based Data Mining Methods, the First International Symposium on Financial Information Processing, May 27-28, 2008, Shanghai, China
Multiple Criteria Mathematical Programming-based Data Mining - Theory and Applications, IEEE Data Mining Forum 2008, May 28-29, 2008, Hong Kong, China
Credit Scoring and Its Impact on China’s Economy, the International Symposium on Financial Engineering and Risk Management (FERM 2008), June 6-10, 2008, Shanghai, China
Multiple Criteria Mathematical Programming and Data Mining, the International Conference on Computational Science, June 23-25, 2008, Krakow, Poland
From Data Mining to Intelligent Knowledge Management, the International Conference on Information and Business Management, March 29-April 1, 2009, Dubai, UAE
Linear Programming Extensions and Applications in Data Mining, the International Conference on Linear Programming Algorithms and Extensions, May 24-26, 2009, Haikou, Hainan Island, China,
Multiple Criteria Mathematical Programming and Its Real-life Applications, Georg Cantor Award speech at 20th International Conference on Multiple Criteria Decision Making, Chengdu, China, June 21-26, 2009, Chengdu, China
My Key Contribution in Multiple Criteria Decision Making, Data Mining and Intelligent Knowledge Management, the Fudan Premium Fund of Management, July 18-19, 2009, Shanghai, China
Acceptance Speech for Fudan Prize of Distinguished Contribution in Management, the Fudan Premium Fund of Management, Nov. 1, 2009, Beijing, China
Intelligent Knowledge: A Study beyond Data Mining, the 2nd International Conference on Software Engineering and Data Mining, June 23, 2010, Chengdu, China.
Finding Intelligent Knowledge beyond Data Mining and Human Experience, the First Symposium of Risk Analysis and Risk Management in Western China, June 26, 2010, Guiyang, China.
Optimization-based Data Mining and Intelligent Knowledge, the IBM China Research Center 15th Celebration Conference, Sept. 15, 2010, Beijing, China.
Multiple Criteria Programming-based Data Mining Methods and Intelligent Knowledge Research, 2010 Workshop on Optimization Based Methods for Emerging Data MiningProblems (OEDM'10), the 2010 IEEE International Conference on Data Mining, Dec. 14, Sydney, Australia.
Can Studies on Data Related Issues Be “Data Science”? the Second International Symposium on Dataology& Data Science, May 29-30, 2011, Beijing, China.
Challenging Problems in Data Science: Big Data, Deep Web and Intelligent Knowledge, the Third International Symposium on Dataology& Data Science, May 20-21, 2012, Kunming, China.
Big Data, Data Science and Economic Development, the 424 XiangshanScience Conference, May 22-24, 2012, Beijing, China.
Big Data and Decision Making, The Second International Symposium on System Information andEngineering 2013 (ISSIE 2013), July 8-9, 2013, Xi'an, China.
Big Data Mining and Challenges to Management Science, the 462 Xiangshan ScienceConference, May 29-31, 2013, Beijing, China.
Optimization based Data Mining, Intelligent Knowledge and Big Data, The3rd International Conference on Business Computing and Global Informatization (BCGIn 2013), Sept. 13-15, 2013, Changsha, China.
Big Data, Big Data Mining and Data Science, 5th International Conference on Computers Communications and Control, ICCCC 2014, Băile Felix, Oradea, Romania, May 7-9, 2014.
Big Data Mining and Applications, 2014 International Conference on Big Data, Beijing, China, August 19-20, 2014.
Big Data Analysis: Research and Exchanges around the World, the 27th General Meeting of the World Academy of Sciences for Advancement of Science in Developing Countries, Kigali, Rwanda, November 14-17, 2016.
Big Data Analysis and The Belt-the Road Initiative, the 2017 China Big Data Expo, Guiyang, China, May 24-25, 2017.
Credit Scoring and Big Data Analysis, the 2017 New Moganshan Conference, Zhengjiang, China, September 15-16, 2017.
Big Data Analysis and Its Applications, the 2017 Symposium on Smart City Theory and Practice, Hong Kong, China, September 25-27, 2017.
Big Data and Education, the 2017 Second International Forum for Big Data Education, Shangdong, China, November 10-11, 2017.
Big Data Analysis and Personnel Training, the 2017 Big Data Personnel Training Summit, Hainan, China, December 1-3, 2017.
Data Science and Course Development, the 2017 Symposium on Data Science and Big Data Personnel Training, Xian, China, December 23, 2017.
Optimization based Dara Mining: Theory, Methods and Applications, the 2018Annual Meeting of Chinese Academy of Sciences, Beijing, China, May 31, 2018.
From AHP to Creativity in China, the 2018 International Symposium on Analytic Hierarchy Process (ISAHP 2018), Hong Kong, July 13-15, 2018.
Big Data Analysis and the Belt and Road Initiative, the 17th Western China international Fair, Chengdu, China, September 20, 2018.
Big Data Analysis and the Belt and Road Initiative, The 26th Annual Conference on Pacific Basin Finance, Economics, Accounting, and Management, Rutgers University, USA, September 6-7, 2018,
Big Data Analytics: Theory and Applications, the IEEE/WIC/ACM International Conference on Web Intelligence 2018 (WI'18), Santiago, Chile, December 3-6, 2018.
Optimization based Data Mining and Bioinformatics, The Sixth International Conference on Data Science (ICDS 2019), Ningbo, China, May 18, 2019.
Big Data Analysis Theory and Applications, The 12th International Conference on Large-Scale Scientific Computations, Sozopol, Bulgaria, June 10, 2019.
Value Investment in Global COVID-19 Pandemic: Challenge and Opportunity, The Fifth Sino-American Venture Capital Summit (SAVCS 2020), Omaha, USA, May 1, 2020.
How to Deal with COVID-19 by using Data Analysis, The Seventh International Conference on Data Science (ICDS 2020), Chengdu, China, December 26, 2020.
Digital Economy: History, Development and Future Trends, The Tenth International Conference on Information Technology and Quantitative Management (ITQM 2023), Oxford, UK, August 12, 2023.
INVITED RESEARCH SPEECHES AT INSTITUTIONS
Has been invited to visit and/or give research lectures on various topics at the following international campuses, institutes or professional societies during 1993-2018:
1. Guizhou Economic Mathematics Research Association, China (June 1993)
2. Computing Center, Chinese Academy of Sciences (August 1993)
3. Southwestern Petroleum Institute, China (summers of 1993-1998, November 1998,
May 2000, Oct. 2012)
4. Chengdu University of Science and Technology, China (June 1993, June 1995)
5. Sichuan University, China (June 1995, September 1998, Summer 2001)
6. Southwest Jiao Tong University, China (June 1994)
7. Chinese University of Electronic Sciences, Chengdu, China (June 1997, May 2000,
December 2000, Summer 2001, Summer 2019)
8. Institute of System Science, Chinese Academy of Sciences (summers of 1994-1997,
December 1998)
9. Chongqing University of Posts and Telecommunication, China (June 1996, September
1998, August 2002)
10. University of Petroleum at Beijing, China (June 1997)
11. Xi’an Petroleum Institute, China (June 1997)
12. Daqing Petroleum Institute, China (June 1997, December 1998)
13. Jianghan Petroleum Institute, China (November 1998)
14. Development Research Center of the State Council, China (December 1998)
15. Korea Advanced Institute of Science and Technology, Seoul, Korea (August 1998, May 2000,
Feb. 2007, Feb. 2013, August 2013)
16. IEEE Computer Society, Buffalo, NY Chapter (April 1999)
17. IEEE Computer Society, Rochester, NY Chapter (April 1999)
18. Development Research Center of the State Council, China (August 1999)
19. National Chiao Tung University, Taiwan (August 1999)
20. National Taiwan University, Taiwan (August 1999)
21. Institute of Policy and Management, Chinese Academy of Sciences (Summer 2000,
December 2000, Summer 2001, December 2001, March 2002,
July-August 2002, December 2002, March 2003, August 2003)
22. Institute of Software, Chinese Academy of Sciences (Summer 2001)
23. Institute of Computing Technology, Chinese Academy of Sciences (Summer 2001)
24. Institute of Automation, Chinese Academy of Sciences (Summer 2001)
25. Xian Jiaotong University, China (March 2003)
26. Fudan University, China (March 2003, July 2007)
27. Sichuan University, China (March 2003)
27. Institute of Control Sciences, Institute of System Analysis and Computing Center,
Russian Academy of Sciences (May 2003)
28. Tsinghua University, China (August 2003)
29. Institute of Remote Sensing Applications, Chinese Academy of Sciences (November 2003,
November 2004)
30. Graduate School of Chinese Academy of Sciences (January 2004)
31. Rensselaer Polytechnic Institute, Troy, New York (February 2004)
32. McMaster University, Canada (April 2004)
33. Duke University (April 2004, November 2004)
34. Southern Methodist University (April 2004)
35. Hirosaki University, Japan (February 2005)
36. University of Chicago (April 2006)
37. University of Cambridge, UK (May 2006)
38. Purdue University, USA (September 2006)
39. University of Colorado, Boulder, USA (October 2006)
40. Dalian University of Science and Technology, China (Jan. 2007)
41. Nanjing University, China (April 2007)
42. Fudan University, China (July 2007)
43. University of Minnesota, USA (Sept. 2007)
44. Xi’an Jiaotong University, China (Jan. 2008, March 2013)
45. Zhongshan University, China (March 2008)
46. Princeton University, USA (April 2008)
47. Ohio State University, USA (September 2008)
48. Fuzhou University, China (November 2009)
49. Southwestern University of Finance and Economics, China (December 2009)
50. University of Miami, USA (December 2009)
51. York University, Canada (September 2010)
52. The Australia e-Health Research Centre, ICT Centre, CSIRO, Brisbane, Australia (July 2011)
53. Tasmanian ICT Centre, CSIRO, Tasmania, Australia (July 2011)
54. Texas State University-San Marcos, USA (Sept. 2011)
55. Rutgers State University, USA (March 2012, February 2024)
56. Southwest Petroleum University, China (June 2012)
57. Brunel University, UK (August 2012)
58. University of Pittsburgh, USA (January 2013)
59. Wuhan University, China (May 2013)
60. Barcelona Super Computing Center, Spain (June 2013, January 2014)
61. University of Granada, Spain (June 2013)
62. Institute of Computing Science, Poznań University of Technology, Poland (January 2014)
63. Agora University, Romania (May 2014)
64. Higher School of Economics, National Research University, Russia (June 2014)
65. Romania Academy of Sciences, Romania (June 2014)
66. University of Belgrade, Siberia (May 2015)
67. Hoseo University, Korea (October 2015, February 2016)
68. Kunming University of Science and Technology, China (May 2016)
69. Zhejiang University, China (July 2016)
70. University of Science and Technology of China, China (July 2016)
71. Nanchang University, China (Jan. 2017)
72. Massachusetts Institute of Technology (February 2017)
73. University of Pittsburg (February2017)
74. Ningbao Hightech Institute, China (March 2017)
75. Wuxi National Supercomputing Center (March 2017)
76. China Fortune Land Development Co., Ltd, China (May 2017)
77. Guian Hightech Institute, China (May 2017)
78. GanjiangHightech Institute, China (June 2017)
79. Suzhou University, China (June 2017)
80. Tangshan Hightech Institute, China (July 2017)
81. The people's Government of the Tujia and Miao Autonomous Prefecture of Xiangxi, China (July 2017)
82.Geochemistry Institute of the Chinese Academy of Sciences, Guiyang, China (July 2017)
83. Xian International University, China (July 2017)
84. Southwest Minzu University, China (September 2017, Summer 2019)
85. Polytech University of Hong Kong (September 2017)
86. Tecnológico de Monterrey, Mexico (October 2017)
87. California Institute of Technology (October 2017)
88. Wuhan University, China (December 2017)
85. Polytech University of Hong Kong (September 2017)
86. Chengdu Association of Science and Technology (September 2018)
87. Southwest Minority University, China (December 2018)
88. Beijing University of International Trade and Economics, China (December 2018)
89. Central University of Finance and Economics, Beijing, China (December 2019)
90. Beijing Technology and Business University, China (December 2019)
91. University of Miami (December 2020)
92. Chinese University of Hong Kong (May 2024)
93. South University of Science and Technology, China (December 2024)
94. University of California, Riverside (January 2025)
PUBLICATIONS
Books:
40. What is Intelligence: A Theory of General Artificial Intelligence, (Edited by Zhong, Y., He, H., Wang, P., Shi, Y., Qu, Y., Wang, Y), EDP Sciences Press, 2025,
39. Proceedings of Twelfth International Conference on Information Technology and Quantitative Management, (Edited byShi, Y., Filip, F.G., He, J., Li, J.P., Tien, J., Berg, D.), Newark, New Jersey, USA, August 15-17, 2025, Procedia Computer Science/Elsevier, Pages 1-1442.
38. Channel Computing Resourcesfrom the East to the Westand the Digital Economy, (Edited by Shi, Y., Li, B., Kou, G., Guo, K.) Posts & Telecom Press, ISBN: 9787115654892, 2024, Pages 1-136. (in Chinese).
37. Proceedings of Eleventh International Conference on Information Technology and Quantitative Management, (Edited byShi, Y., Filip, F.G., He, J., Li, J.P., Tien, J., Berg, D.), Bucharest, Romania, August 23-25, 2024, Procedia Computer Science/Elsevier, Vol. 242, Pages 1-1460.
36. Proceedings of Tenth International Conference on Information Technology and Quantitative Management, (Edited byShi, Y., Filip, F.G., He, J., Li, J.P., Tien, J., Berg, D.), Oxford, UK, August 12-14, 2023, Procedia Computer Science/Elsevier, Vol. 221, Pages 1-1546.
35. Proceedings of Ninth International Conference on Information Technology and Quantitative Management, (Edited byShi, Y., Li, J., Kou, G, Berg, D., Tien, J.), Beijing, China, December 9-11, 2022, Procedia Computer Science/Elsevier, Vol. 214, Pages 1-1624.
34. Advances in Big Data Analytics: Theory, Algorithm and Practice, Springer, 2022, 728 pages.
33. Proceedings of Eighth International Conference on Information Technology and Quantitative Management, (Edited by Liu, Y.B., Shi, Y., Wang, Y., Ergu, D., Berg, D., Tien, J., Li, J., Tian, Y.J.), Chengdu, China, July 9-11, Procedia Computer Science/Elsevier, Vol. 199, Pages 1-1522.
32.Proceedings of Sixth International Conference on Data Science, (Edited by Jing He, Philip S. Yu,YongShi, Xingsen Li, Zhijun Xie, Guangyan Huang, Jie Cao, Fu Xiao), Ningbo, China, Springer, LNCS 9208, Pages 1-708, 2019.
31. Proceedings of Seventh International Conference on Information Technology and Quantitative Management, (Edited by Herrera-Viedma, E., Shi, Y., Berg, D., Tien, J., Cabrerizo, F. J., Li, J.), Granada, Spain, November 3-6, 2019, Procedia Computer Science/Elsevier, Vol. 162, Pages 1-990.
30. Proceedings of Sixth International Conference on Information Technology and Quantitative Management, (Edited by Shi, Y., Wolcott, P., Kwak, W., Chen, Z. Tian, Y.J., Lee, H.), Omaha, USA, October 20-21, 2018, Procedia Computer Science/Elsevier, Vol. 139, Pages 1-634.
29. Computational Science – ICCS 2018 (PartI-III), 18th International Conference on Computational Science Proceedings (Edited by Yong Shi, Haohuan Fu, Yingjie Tian, Michael Lees, V. Krzhizhanovskaya, Jack Dongarraand Peter Sloot), Wuxi, China,June 11-13, Springer,2018, 2100 pages.
28. Proceedings of Fifth International Conference on Information Technology and Quantitative Management,(Edited by Ahuja, V., Shi, Y., Khazanchi, D., Abidi, N., Tian, Y., Berg, D., Tien, J.), New Delhi, India, December 8-10, 2017, Procedia Computer Science/Elsevier, Vol. 122, Pages 1-1196.
27.Proceedings of International Conference on Brain Informatics and Health, (Edited by Giorgio A. Ascoli, Michael Hawrykycz, Hesham Ali, Deepak Khazanchi and Yong Shi), Omaha, NE, USA, October 13-16, 2016, Springer, LNAI 9919, Pages 1-388.
26.Proceedings of Forth International Conference on Information Technology and Quantitative Management, (Edited by Heeseok Lee, Yong Shi, Jongwon Lee, Felisa Cordova, Ioan Dzitac, Gang Kouand Jaiping Li), Asan, Korea, August 16-18, 2016, Procedia Computer Science, Volume 91, Pages 1-1146.
25.Proceedings of Second International Conference on Data Science, (Edited by Chengqi Zhang, Wei Huang, Yong Shi, Philip S. Yu, Yangyong Zhu, Yingjie Tian, Peng Zhang and Jing He), Sydney, Australia, Springer, LNCS 9208, Pages 1-194, 2015.
24.Proceedings of Third International Conference on Information Technology and Quantitative Management, (Edited by L.F.A.M. Gomes, Y. Shi, R. Colcher, P. Wolcott, E. Herrera-Viedma), Rio, Brazil, July 21-24, Procedia Computer Science, Volume 55, Pages 1-1426, 2015.
23. Intelligent Knowledge: A Study beyond Data Mining(with L. Zhang, Y. Tian, X. Li), Springer, 2015, 150pages.
22.Proceedings of Second International Conference on Information Technology and Quantitative Management, (Edited by FuadAleskerov, Yong Shi and Alexander Lepskiy), Moscow, Russia, June 3-5, Procedia Computer Science, Volume 31, Pages 1-1176, 2014.
21.Proceedings of First International Conference on Information Technology and Quantitative Management, (Edited by Yong Shi, Youmin Xi, Peter Wolcott, Yingjie Tian, Jianping Li, Daniel Berg, Zhengxin Chen, Enrique Herrera-Viedma, Gang Kou, Heeseok Lee, Yi Peng and Lean Yu), Suzhou, China, May 16-18, Procedia Computer Science, Volume 17, Pages 1-1282, 2013.
20. 12th International Conference on Computational Science Proceedings (with Hesham Ali, Deepak Khazanchi, Michael Lees, Geert Dick van Albada, Peter Sloot and Jack Dongarra), Omaha, Nebraska,June 4-6, Procedia Computer Science, 2012, 2024 pages.
19. Data Processing for the AHP/ANP (with G. Kou, D. Ergu, Y. Peng),Springer, 2012, 145 pages.
18. Optimization based Data Mining: Theory and Applications (with Y.J.Tian, G. Kou, Y. Peng, and J. P. Li), Springer, 2011, 331 pages.
17. New State of MCDM in 21st Century: Proceeding of the 20th International Conference on
Multiple Criteria Decision Making (with S. Wang, G. Kou and J. Wallenius), Springer, Lecture Notes in Economics and Mathematical Systems, 2011, 211 pages.
16. China’s Reality and Global Vision (with Siwei Cheng, Cunjun Zhao and Xiaohong Chen), World Scientific Publishing, October 2009, 300 pages.
15. Cutting-Edge Research Topics on Multiple Criteria Decision Making (with Shouyang Wang, Yi Peng, Jiaping Li and Yong Zeng), Springer, CCIS 35, 2009, 852 pages.
14. Advanced Web and Network Technologies, and Applications, (with Y. Ishikawa, J. He, G. Xu, G. Huang, C. Pang, Q. Zhang, G. Wang), Springer, APWeb 2008, 300 pages.
13. Communications and Discoveries from Multidisciplinary Data (with Shuichi Iwata, Yukio Ohsawa, Shusaku Tsumoto, Ning Zhong and Lorenzo Magnani) , Springer, Studies in Computational Intelligence 123, 2008, 340 pages.
12. 2007 IEEE International Conference on Data Mining Proceedings（with N. Ramakrishnan, O. R. Zaïane, C. Cliftion, and X. Wu), IEEE Computer Society Press, California, USA, 2007, 771 pages.
11. 2007 IEEE International Conference on Data Mining Workshops（with A. K .H. Tung, Q. Zhu, N. Ramakrishnan, O. R. Zaïane, C. Cliftion, and X. Wu), IEEE Computer Society Press, California, USA, 2007, 734 pages.
10. 7th International Conference on Computational Science Proceedings (with Geert Dick van Albada, Jack Dongarra, and Peter Sloot), Beijing, May 27-30, LNCS 4487-4490, Springer, 2007, 3600 pages.
9. Knowledge and Wisdom: Advances in Multiple Criteria Decision Making and Human Systems Management (with David L. Olson and Antonie Stam), IOS Press, 2007, 400 pages.
8. Multiple Criteria Linear Programming Decision Systems: Theory and Applications, (with Y. Zhong, J. Zhang and Y. Liu), (in Chinese), Chinese High Education Press, 2007, 540 pages.
7. Introduction to Business Data Mining, (with David Olson), McGraw-Hill/Irwin, 2007, 273 pages.
6. Towards Efficient Fuzzy Information Processing Using Principle of Information Diffusion, (with Chongfu Huang), Springer-Verlag, May 2002, 263 pages.
5. Multiple Criteria Multiple Constraint-level (MC2) Linear Programming: Concepts, Techniques and Applications, World Scientific Publishing, May 2001, 539 pages.
4. New Frontiers of Decision Making for the Information Technology Era, (with M. Zeleny), World Scientific Publishing, May 2000, 420 pages.
3. Data Ming and Knowledge Management: Chinese Academy of Sciences Symposium (CASDMKM 2004), (with W. Xu and Z. Chen), LNAI 3327, Springer-Verlag, 2004, 263 pages.
2. Quantitative Foundations for Information Technology, (with H. Farhat and L. Najjar), Pearson Custom Publishing, December 2000, 239 pages.
1. Operations Research in Management, Southwestern Petroleum Institute Press, China,
1983, 240 pages (in Chinese).
(SCI/SSCI: 196, EI: 32, ISTP: 3, INSPEC: 37, MathSci: 25, Cabell: 2)
249. Li, M., Shi, Y. “Dataset Distillation: Recent Advances of Methods and Challenges”,Annals of Data Science, 2025. (EI).
248. Y. Shi, T. Yao. "ESG Rating Divergence: Existence, Driving Factors, and Impact Effects",Sustainability, 17(10), 4717,2025.(SSCI).
247. Y. Shi, Y. Qu, Z. Chen, Y. Mi, Y. Wang, “Improved Credit Risk Prediction Based on an Integrated Graph Representation Learning Approach with Graph Transformation,” European Journal of Operational Research, Vol.315, No.2, 786–801, 2024. (SCI).
246. Y. Shi, Y. Qu, L. Zhang, “How China Deals With COVID-19 Pandemic,” International Journal of Information Technology & Decision Making, Vol.23, No.01, 17–35, 2024. (SCI).
245. P. Quan, L. Zheng, W. Zhang, Y. Xiao, L. Niu, Y. Shi, “ExGAT: Context extended graph attention neural network,” Neural Networks, 181, 106784, 2025. (SCI).
244. Y. Shi, L. Zheng, P. Quan, Y. Xiao, L. Niu, “A universal network strategy for lightspeed computation of entropy-regularized optimal transport,” Neural Networks, 107038, 2024. (SCI).
243. J. Miao, J. Zhao, T. Yang, C. Fan, Y. Tian, Y. Shi, M. Xu, “Explicit unsupervised feature selection based on structured graph and locally linear embedding,” Expert Systems with Applications, 255, 124568, 2024. (SCI).
242. B. Li, J. Feng, Y. Yan, G. Kou, H. Li, Y. Du, X. Wang, T. Li, Y. Peng, K. Guo, Y. Shi, “Building a Chinese ancient architecture multimodal dataset combining image, annotation and style-model,” Scientific Data, 11 (1), 1137, 2024. (SCI).
241. C. Venkatesan, Y. D. Zhang, C. C. Onn, Y. Shi, “Introduction to the Special Issue on Next Generation Pervasive Reconfigurable Computing for High Performance Real-Time Applications,” Scalable Computing: Practice and Experience, 25 (5), 4407-4410, 2024. (SCI).
240. F. Liu, D. Ergu, B. Li, W. Deng, Z. Chen, G. Lu, Y. Shi, “A Text Mining Approach to Covid-19 Literature,” International Journal of Information Technology & Decision Making, 23 (04), 2024. (SCI).
239. Y. Mi, Z. Wang, P. Quan, Y. Shi, “A semi-supervised concept-cognitive computing system for dynamic classification decision making with limited feedback information,” European Journal of Operational Research, 315 (3), 1123-1138, 2024. (SCI).
238. Y. Shi, L. Zheng, P. Quan, L. Niu, “Wasserstein distance regularized graph neural networks,” Information Sciences, 670, 120608, 2024. (SCI).
237. Y. Shi, E. Eremina, W. Long, “Machine learning models for early‐stage investment decision making in startups,” Managerial and Decision Economics, 45 (3), 1259-1279, 2024. (SSCI).
236. Y. Shi, A. Tang, L. Niu, R. Zhou, “Sparse optimization guided pruning for neural networks,” Neurocomputing, 574, 127280, 2024. (SCI).
235. H. Liao, X. Jin, Y. Shi, G. Kou, “A Bibliometric Overview and Visualization of the International Journal of Information Technology and Decision Making Between 2012 and 2022,” International Journal of Information Technology & Decision Making, 23 (01), 2024. (SCI).
234. J. M. Tien, Y. Shi, J. Li, “Guest Editors’ Introduction for the Special Issue on The Role of Decision Making to Overcome COVID-19,” International Journal of Information Technology & Decision Making, 23 (01), 1-4, 2024. (SCI).
233. Y. Shi, Y. Wang, Y. Qu, Z. Chen, “Integrated GCN-LSTM stock prices movement prediction based on knowledge-incorporated graphs construction,” International Journal of Machine Learning and Cybernetics, 15 (1), 161-176, 2024. (SCI).
232. B. Li, G. Kou, H. Li, K. Guo, Y. Shi, “Document meaning behind China’s cultural relics,” Science, 382 (6675), 1130-1130, 2023. (SCI).
231. L. Zhang, Y. Shi, “Sparse and semi-attention guided faults diagnosis approach for distributed online services,” Applied Soft Computing, 148, 110911, 2023. (SCI).
230. Y. Shi, G. Kou, B. Li, “Analysis and research on the strategy andproblems of “Channel Computing Resourcesfrom the East to the West”” Big Data Research, 9 (5), 3-8, 2023(in Chinese)
229. Y. Shi, Y. Zhang, P. Zhang, Y. Xiao, L. Niu, “Federated learning with ℓ1 regularization,” Pattern Recognition Letters, 172, 15-21, 2023 (SCI)
228. F. Liu, N. Damen, Z. Chen, Y. Shi, S. Guan, D. Ergu, “Identifying Smart City Leaders and Followers with Machine Learning,” Sustainability, 15 (12), 9671, 2023 (SCI)
227. J. He, H. Zheng, R. Zarei, H. C. Lui, Q. W. Kong, Y. M. Ji, X. Li, H. Yang, B. Du, ... , “Linear Step-adjusting Programming in Factor Space,” International Journal of Information Technology & Decision Making, 1-22, 2023 (SCI)
226. P. Karrupusamy, H. M. Wee, Y. Shi, “Multimedia and multimodal sensing for personalized healthcare,” Personal and Ubiquitous Computing, 27 (3), 887-888, 2023
225. Z. Zhang, J. He, H. Zheng, J. Cao, G. Wang, Y. Shi, “Alternating minimization-based sparse least-squares classifier for accuracy and interpretability improvement of credit risk assessment,” International Journal of Information Technology & Decision Making, 22 (01), 2023 (SCI)
224. W. Kwak, X. Cheng, Y. Shi, F. Liu, K. Kwak, “Auditor Change Prediction Using Data Mining and Audit Reports,” Encyclopedia of Data Science and Machine Learning, 1-13, 2023 (SCI)
223. Y. Shi, A. Tang, Y. Xiao, L. Niu, “A lightweight network for COVID-19 detection in X-ray images,” Methods, 209, 29-37, 2023 (SCI)
222. J. Liu, H. Hang, B. Wang, B. Li, H. Wang, Y, Tian, Y. Shi, “GAN-CL: Generative Adversarial Networks for Learning From Complementary Labels”, IEEE Transactions on Cybernetics, 53(1), 236-247, 2023 (SCI)
221. Y. Shi, P. Quan, Y. Xiao, M. Lei, L. Liu, “Graph Influence Network”, IEEE Transactions on Cybernetics, 53(10), 6146 – 6159, 2023 (SCI)
220. Y. Shi, “Digital Economy: Development and Future”, Bulletin of Chinese Academy of Sciences, 2022, 37(1): 78-87
219. H. Li, Z. Wang, J. Cao, J. Pei, Y. Shi, “Optimal Estimation of Low-Rank Factors via Feature Level Data Fusion of Multiplex Signal Systems”, IEEE Transactions on Knowledge and Data Engineering, 34(6), 2860-2871, 2022 (SCI)
218. J. Liu, B. Wang, H. Hang, H.Wang, Z. Qi, Y. Tian, Y. Shi, “LLP-GAN: A GAN-Based Algorithm for Learning from Label Proportions,” IEEE Transactions on Neural Networks and Learning Systems, 2022, doi: 10.1109/TNNLS.2022.3149926 (SCI) (
217. Mi, Y., W. Liu, Y. Shi, J. Li, “Semi-Supervised Concept Learning by Concept-Cognitive Learning and Concept Space’, IEEE Transactions on Knowledge and Data Engineering, 34(5), 2429-2442, 2022 (SCI)
216.Mi, Y., Quan, P., Ma, R., Shi, Y., Nie, L., “DigGCN: Learning Compact Graph Convolutional Networks via Diffusion Aggregation,”IEEE Transactions on Cybernetics,52 (2), 912-924, 2022 (SCI)
215. Mi, Y., Shi, Y., Li., J., Liu, W. and Yan, M., “Fuzzy-Based Concept Learning Method: ExploitingData with Fuzzy Conceptual Clustering”, IEEE Transactions on Cybernetics, 52(1), 582-593, 2022 (SCI)
214. J. Miao, T. Yang, L. Sun, L. Niu, Y. Shi, “Towards Compact Broad Learning System by Combined Sparse Regularization”, International Journal of Information Technology and Decision Making, 21(1), 169-194, 2022 (SCI)
213. Y. Shi, Y. Zheng, K. Guo, X. Ren, “Relationship Between Herd Behavior and Chinese Stock Market Fluctuations During a Bullish Period Based on Complex Networks”, International Journal of Information Technology and Decision Making, 2021 (SCI)
212.Y. Shi, W. Dai, W. Long, B. Li, “A New Deep Learning-Based Zero-Inflated Duration Model for Financial Data Irregularly Spaced in Time”, Frontiers in Physics, 2021, doi.org/10.3389/fphy.2021.651528. (SCI)
211.Y. Shi, W. Dai, W. Long, B. Li, “Improved ACD-Based Financial Trade Durations Prediction Leveraging LSTM Networks and Attention Mechanism”, Mathematical Problems in Engineering, DOI: 10.1155/2021/7854512, 2021, (SCI)
210. Y. Shi, J. Yang, Z. Qi, “Unsupervised Anomaly Segmentation via Deep Feature Reconstruction”, Neurocomputing, 424 (1), 9-22, 2021. (SCI)
209. H. Tang, P. Dong, Y. Shi, “A Construction of Robust Representation for Small Data Sets Using Broad Learning System”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2021, 51 (10), 6074-6084. (SCI)
208. Y. Shi, “My Early Researches on Fuzzy Set and Fuzzy Logic”, Int. J. Comput. Commun. Control, 16(1), 2020.
207. Y. Liu,Z. Gu,S. Xia,B. Shi,X. Zhou,Y. Shi, J. Liu, “What are the Underlying Transmission Patterns of COVID-19 Outbreak? An Age-Specific Social Contact Characterization”, EClincialMedicine, Vol. 22, May 01, 2020.
206.W. Wu, Z. Xu, G. Kou and Y. Shi, “Decision-Making Support for the Evaluation of ClusteringAlgorithms Based on MCDM,”Complexity,https://doi.org/10.1155/2020/9602526, Vol. 2020. (SCI).
205. Li, T., Kou, G., Peng, P. and Shi, Y., “Classifying with Adaptive Hyper-Spheres: An Incremental Classifier Based on Competitive Learning”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 50(4), April 2020, 1218-1229. (SCI).
204. Shi, Y., Miao, J. and Niu, F., “Feature Selection with MCP2 Regularization”, Neural Computing and Applications, 2019, 31:6699-6709 (SCI).
203. Zhang F., Liu J., Wang Bo, Qi Z. and Shi Y., “A Fast Algorithm for Multi-Class Learning from Label Proportions”, Electronics, 2019,8(6):609. (SCI).
202. Shi Y.,Ye-ran Tang,Wen Long, “Sentiment contagion analysis of interacting investors: Evidence from China’s stock forum”, Physica A: Statistical Mechanics and its Applications, 2019, 523:246-259. (SCI).
201. Shi Y., Lei M, Zhang P, Niu L. F., “Diffusion Based Network Embedding”, Pattern Recognition, Vol. 88, April 2019, 518-531. (SCI).
200. Liu F., Peng Y., Chen Z., Shi Y., “Modeling of Characteristics on Artificial Intelligence IQ Test: A Fuzzy Cognitive Map-Based Dynamic Scenario Analysis”, International Journal of Computers Communications and Control, 2019, 14(6), 653-669. (SCI).
199. Shi Y., Zhu L., Li W., Guo K., Zheng Y., “Survey on Latest Textual Sentiment Analysis Articles and Techniques”, International Journal of Information Technology and Decision Making, 2019, 18(4), 1243-1287. (SCI).
198. Deng W., Shi Y., Chen Z., Kwak W., Tang H, “Recommender System for Marketing Optimization”, World Wide Web, 2019, 1-21. (SCI).
197.Tang H., Dong P., Shi Y., “A New Approach of Integrating Piecewise Linear Representation and Weighted Support Vector Machine for Forecasting Stock Turning Points”, Applied Soft Computing, 2019, 78: 685-696. (SCI).
196. Tang H., Shi Y., Dong P., “Public Blockchain Evaluation using Entropy and TOPSIS”, Expert Systems with Applications, 2019, 117: 204-210. (SCI).
195. Shi Y., Mi Y., Li J., Liu, W., “Concurrent Concept-cognitive Learning Model for Classification”, Information Sciences, 2019, 496: 65-81. (SCI).
194. Shi Y., Li B., Wang B., Qi Z., Liu. J, “Unsupervised Single-Image Super-Resolution with Multi-Gram Loss”, Electronics, 2019,8(8):833. (SCI).
193. Shi Y., Li B., Long W., “Pyramid Scheme Model for Consumption Rebate Frauds”, Chinese Physics B,2019,28(07):553-560. (SCI).
192. Qi, Z., Meng, F., Tian, Y., Niu, L., Shi, Y. and Zhang, P., “Adaboost-LLP: A Boosting Method for Learning with Label Proportions”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 29, No. 8, 3548-3559, 2018. (SCI, IF 11.68).
191. Shi Y., Li P., Yu X., Wang H., Niu L., “Evaluating Doctor Performance: Ordinal Regression-Based Approach”,Journal of Medical Internet Research, 2018, Jul 18;20(7): e240. doi: 10.2196/jmir.9300. (SCI).
190. Shi Y., Mi Y., Li J., Liu, W., “Concept-Cognitive Learning Model for Incremental Concept Learning”, IEEE Transactions on Systems, Man, and Cybernetics: Systems, 2018, 1(1):1-13. (SCI).
189. Y.Shi, Tang Y, Cui L, Long W., “A Text Mining Based Study of Investor Sentiment and Its Influence on Stock Returns”, Economic Computation & Economic Cybernetics Studies & Research, 2018, 52(1), 183-199, 2018. (SCI).
188. Li W., Guo K., Shi Y., et al., “Dwwp: Domain-Specific New Words Detection and Word Propagation System for Sentiment Analysis in The Tourism Domain”,Knowledge-Based Systems, Vol.146, pp. 203-214, 2018. (SCI).
187. Shi Y., Liu J., Qi Z., Wang, B., “Learning from Label Proportions on High-Dimensional Data”,Neural Networks, Vol. 103, pp. 9-18, 2018. (SCI).
186. Liu D., Li D., Shi Y., et al., “Large-scale Linear Nonparallel SVMs”,Soft Computing, Vol. 22(6), pp. 1945-1957, 2018. (SCI).
185. Shi Y., Miao J., Wang Z., et al., “Feature Selection with ℓ2, 1-2 Regularization”, IEEE Transactions on Neural Networks and Learning Systems, Vol. 29(10), pp. 4967-4982, 2018. (SCI).
184. Shi, Y., Shan, Z., Li, J. et al. “How China Deals with Big Data”. Annals of Data Science, Vol. 4 (4), pp. 433-440, 2017.
183.Shi, Y., Cui, L., Chen, Z., Qi, Z., “Learning from Label Proportions with Pinball Loss”, International Journal of Machine Learning and Cybernetics, vol. Vol. 7 (3), pp. 1-19, 2017.(SCI).
182. Liu, F., Shi, Y., Liu, Y., “Intelligence Quotient and Intelligence Grade of Artificial Intelligence”, Annals of Data Science, vol. Vol. 4 (2), pp. 179–191, 2017.
181. Liu, D., Shi, Y., Y. Tian, Huang, X., “Ramp Loss Least Squares Support Vector Machine”, Journal of Computational Science, Vol. 14, pp. 61-68, 2016. (SCI).
180. Shi Y., L. Cui, Z. Qi, F. Meng and Z. Chen, "Automatic Road Crack Detection Using Random Structured Forests,"IEEE Transactions on Intelligent Transportation Systems, Vol. 17, No. 12:3434-3445, 2016. (SCI).
179. Bamakana, S. M. H., H. D. Wang, Y. Tian, and Y. Shi, "An Effective Intrusion Detection Framework based on MCLP/SVM Optimized by Time-Varying Chaos Particle Swarm Optimization, "Neurocomputing, Vol. 199: 90–102, 2016.(SCI).
178. Tian, Y., X. Ju and Y. Shi, "A Divide-and-Combine Method for Large Scale Nonparallel Support Vector Machines," Neural Networks, Vol. 7:12-21, 2016. (SCI).
177. Xu, Z., Shi, Y. Exploring Big Data Analysis: Fundamental Scientific Problems. Annals of Data Science, Vol. 2, pp. 363–372, 2015.
176. Qi, Z., Y. Tian, Y. Shi, and V. Alexandrov, “Parallel RMCLP Classification Algorithm and Its Application on the Medical Data”, IEEE Transactions on Cloud Computing, 2015, 2481381. (SCI).
175. Shi, Y., Z.F. Yang, H. Yan, X. Tian, “Delivery Efficiency and Supplier Performance Evaluation in China's E-retailing Industry”, Journal of Systems Science and Complexity, 2015, to appear.(SCI).
174. Qi, Z., Y. Tian, and Y. Shi, “Successive Overrelaxation for Laplacian Support Vector Machine,” IEEE Transactions on Neural Networks and Learning Systems, Vol. 26(4), pp. 674-683, 2015. (SCI).
173. H. Wang, S. Guo, S. Bamakan, and Y. Shi, “Homeomorphism Problems of Fuzzy Real Number Space and the Space of Bounded Functions with Same Monotonicity on [-1, 1],”International Journal of Computers Communications & Control,Vol. 10(6), pp. 129-143, 2015. (SCI).
172. D. Liu, Y. Tian, and Y. Shi, “Ramp Loss Nonparallel Support Vector Machine for Pattern Classification,”Knowledge-Based Systems, Vol. 85, pp. 224-233, 2015. (SCI).
171. F. Liu, Y. Shi, and B. Wang, “World Search Engine IQ Test Based on the Internet IQ Evaluation Algorithms,”International Journal of Information Technology & Decision Making,Vol. 14(02), pp. 221-237, 2015. (SCI).
170. L. Niu, R. Zhou, X. Zhao, and Y. Shi, “Two New Decomposition Algorithms for Training Bound-Constrained Support Vector Machines,” Foundations of Computing and Decision Sciences,Vol. 40(1), pp.67-86, 2015. (SCI).
169.X. Zhao, Y. Shi, and L. Niu, “Kernel based Simple Regularized Multiple Criteria Linear Program for Binary Classification and Regression,” Intelligent Data Analysis, Vol.19(3), pp.505-527, 2015. (SCI).
168. Li, F.H., J. He, G.Y. Huang, Y.C. Zhang, Y. Shi, R. Zhou, “Node Coupling Clustering Approaches for Link Prediction,” Knowledge-based Systems, Vol. 89, 2015, pp. 669-680. (SCI).
167. Lee, J.W., Y. Shi, F. Wang, H. S. Lee, and H. K., Kim, “Advertisement Clicking Prediction by Using Multiple Criteria Mathematical Programming,” The World Wide Web Journal, May, 2015. (SCI).
166. Shi,Y., “Big Data: History, Current Status, and Challenges Going Forward”, The Bridge, The US National Academy of Engineering, Vol. 44(4), Winter 2014, pp. 6-11, 2014.
165. Chen, Y., Y. Shi, X. Wei and L. Zhang, “Domestic Systemically Important Banks: A Quantitative Analysis for the Chinese Banking System”, Mathematical Problems in Engineering, 2014, Article ID 819371. (SCI/SSCI).
164. Chen, Y., Y. Shi, X. Wei and L. Zhang, “How Does Credit Portfolio Diversification Affect Banks’ Return and Risk: Evidence from Chinese Listed Commercial Banks”, Technological and Economic Development of Economy, Vol. 20 (2), pp.332–352, 2014. (SSCI).
163. Qi, Z., Y. Tian, X. Yu and Y. Shi, “A Multi-instance Learning Algorithm based on Nonparallel Classifier,” Applied Mathematics and Computation, Vol.241(15), pp. 233-241,2014. (SCI).
162. Qi, Z., Y. Tian and Y. Shi, “A New Classification Model Using Privileged Information and Its Application”, Neurocomputing, Vol. 129, pp. 146-152,2014. (SCI).
161. Qi, Z., Y. Tian and Y. Shi, “A Nonparallel Support Vector Machine for A Classification Problem with Universum Learning,” J. Computational Applied Mathematics, Vol. 263, pp. 288-298, 2014. (SCI).
160. Qi, Z., Y. Tian and Y. Shi, “Regularized Multiple-Criteria Linear Programming with Universum and Its Application”, Neural Computing and ApplicationsVol. 24(3-4), pp.621-628,2014. (SCI).
159. Tian, Y., X. Ju, Z. Qi and Y. Shi, “Improved Twin Support Vector Machine”, Science China Mathematics, Vol. 57:417-432,2014.(SCI).
158. Y. Tian, Z. Qi, X. Ju, Y. Shi and X. Liu, "Nonparallel Support Vector Machines for Pattern Classification," IEEE Transactions on Cybernetics, Vol. 44(7):1067-79, 2014. (SCI).
157. Zhao, X., Y. Shi, J. Lee, H. H. Kim and H. Lee, “Customer Churn Prediction Based on Feature Clusteringand Nonparallel Support Vector Machine”, International Journal of Information Technology & Decision Making, Vol. 13, 2014, DOI: 10.1142/S0219622014500680. (SCI).
156. Xie, J., J Lei, W Xie, X Guo, Y. Shi and X Liu, “Two-Stage Hybrid Feature Selection Algorithms for Diagnosing Erythemato-Squamous Diseases”, Health Information Science and Systems, Vol. 1(10), 2013. (SCI).
155. Xie, J., K Hone, W Xie, X Gao, Y. Shi, and X Liu, “Extending Twin Support Vector Machine Classifier for Multi-Category Classification Problems”, Intelligent Data Analysis 17(4): 649-664, 2013. (SCI).
154. Liu, R. and Y. Shi, “Spatial Distance Join based Feature Selection”, Engineering Applications of Artificial Intelligence, Vol. 26(10), pp. 2597-2607, 2013.(SCI).
153. Nian, Y., Z. Chen, Y. Shi and Z. Wang, “Using Non-Additive Measure for Optimization-Based Nonlinear Classification”, American Journal of Operations Research, 2012, 2, 364-373 doi:10.4236/ajor.2012.23044.
152. Z. Qi, Y. Tian, and Y. Shi, "Robust Twin Support Vector Machine for Pattern Classification," Pattern Recognition, Vol. 46(1), pp. 305-316, 2013. (SCI).
151. Qi, Z., Y. Tian, and Y. Shi, "Structural Twin Support Vector Machine for Classification," Knowledge-Based Systems, 2013, DOI: 10.1016/j.knosys.2013.01.008. (SCI).
150. Warawut Suphamitmongkol, Guangli Nie, Rong Liu, Sumaporn Kasemsumranand and Yong Shi, “An Alternative Approach for The Classification of Orange Varieties Based on Near Infrared Spectroscopy”, Computers and Electronics in Agriculture, Vol. 91, 87–93, Feb 2013. (SCI).
149. Qi, Z., Y. Tian and Y. Shi, “Multi-Instance Classification Based on Regularized Multiple Criteria Linear Programming,” Neural Computing& Applications, Vol. 23, pp. 857–863, 2013. (SCI).
148. Qi, Z., Y. Tian and Y. Shi, “Efficient Railway Tracks Detection and Turnouts Recognition Method Using HOG Features,” Neural Computing& Applications, Vol. 23, pp. 245–254, 2013.(SCI).
147. Zhang, L., Q. Chen, Y. Chen, Z. Zhu and Y. Shi, “Domain-driven Recommendation Method in Retail Industry,” Intelligent Decisions Technologies Journal, forthcoming.
146. Yan, N., Z. Chen, Y. Shi and Z. Wang, “Using Non-Additive Measure for Optimization-Based Nonlinear Classification”, American Journal of Operations Research, 2012, 2, 364-373 doi:10.4236/ajor.2012.23044.
145. D. Zhang, Y. Tian and Y. Shi, “A Group of Knowledge-Incorporated Multiple Criteria Linear Programming Classifier,” Journal of Computational and Applied Mathematics, Vol. 235, pp. 3705-3717, 2012. (SCI).
144. Qi, Z., Yi. Tian and Y. Shi, “Laplacian Twin Support Vector Machine for Semi-supervised Classification,” Neural Networks, Vol. 35, pp. 46-53, 2012.(SCI).
143. Y. Peng, Y. Zhang, G. Kou, and Y. Shi, “A Multicriteria Decision Making Approach for Estimating the Number of Clusters in a Data Set”, PLoS One, Vol. 7, No.7, 2012. (SCI).
142. G. Kou, Y. Zhao, Y. Pengand Y. Shi, “Multi-Level Opinion Dynamics under Bounded Confidence”, PLoS One, DOI: 10.1371/journal.pone.0043507, Sept. 2012. (SCI).
141. Z. Qi and Y. Shi, “Structural Regular Multiple Criteria Linear Programming for Classification Problem,” International Journal of Computers, Communications & Control, Vol.7, No. 4, 2012. (SCI).
140. L.F. Niu, J. Wu and Y. Shi, “Training the Max-Margin Sequence Model with The Relaxed Slack Variables”, Neural Networks, Vol. 33, pp. 228–235, 2012. (SCI).
139. Y. Liu, L. Zhang, Y. Zhang and Y. Shi, "A Bug Detection Model in Process Monitoring for Trustworthy Software", Journal of Computational Information System, Vol. 8, No. 2, pp. 591-601, 2012. (EI).
138. P. Zhang, B. J. Gao, P. Liu, Y. Shi and L. Guo., “A Framework for Application-Driven Classification of Data Streams”, Neurocomputing, Vol. 92, pp. 170-182, 2012. (SCI).
137. G. Kou, Y. Lu, Y. Peng and Y. Shi, “Evaluation of Classification Algorithms using MCDM and Rank Correlation”, International Journal of Information Technology & Decision Making, DOI: 10.1142/S0219622012500095, Vol. 11, No. 1, 197-225, 2012. (SCI).
136. AG. Lopez-Herrera, E. Herrera-Viedma, MJ. Cobo, MA. Martinez, G. Kou and Y. Shi, “A Conceptual Snapshot of the First Decade (2002-2011) of The International Journal of Information Technology & Decision Making”, International Journal of Information Technology & Decision Making, Vol. 11, No. 2, 247-270, 2012. (SCI).
135. G. Kou, Y. Peng, Y. Shi, and W. Wu, “Classifier Evaluation for Software Defect Prediction”, Studies in Informatics and Control, Vol. 21, No.2, pp. 117-126, 2012. (SCI).
134. Y. Peng, G. Kou, D.Ergu, W. Wu and Y. Shi, “An Integrated Feature Selection and Classification Scheme”, Studies in Informatics and Control, Vol. 21, No. 3, 2012. (SCI).
133. J. He, Y. Zhang, G. Huang and Y. Shi, “Distributed Data Possession Checking for Securing Multiple Replicas in Geographically Dispersed Clouds”, Journal of Computer and System Sciences, Vol. 78, No. 5, 1345-1358, 2012. (SCI).
132. Yan，N.Z. Chen, Y. Shiand Z. Wang, “A Nonlinear Multiregression Model Based on the Choquet Integral with a Quadratic Core, Int. J. Granular Computing, Rough Sets and Intelligent Systems, Vol. 2, No. 3, 244-256, 2012. (SCI).
131. Daji Ergu, Kou, G., Yi Peng, János Fülöp and Yong Shi,“ Further Discussions on Induced Bias Matrix Model of the Pair-wise Comparison Matrix”, Journal of Optimization Theory and Applications, 2012. (SCI).
130. B. Wangand Y. Shi, “Error Correction Method in Classification by Using Multiple-Criteria and Multiple-Constraint Levels Linear Programming”, International Journal of Computers, Communications & Control,Vol.7, No. 5, 976-989, 2012.(SCI).
129. Ergu, D., G. Kou, Y. Peng, F. Li. and Y. Shi, “Consistency in Emergency Management”, International Journal of Computers, Communications & Control, Vol.7, No. 3, 450-458, 2012. (SCI).
128. Y. Tian, Y. Shi and X. Liu, “Recent Advances on Support Vector Machines Research”, Technological and Economic Development of Economy, Vol. 18, No. 1: 5-33 2012. (SSCI).
127. Yi Peng, Gang Kou, DajiErgu, Wenshuai Wu and Yong Shi, “An Integrated Feature Selection and Classification Scheme,” Vol. 21,No.3, Studies in Informatics and Control, 2012.(SCI).
126. Sun, D., L. Liu, P. Zhang, X.Q. Zhu and Y. Shi, “Decision Rule Extraction for Regularized Multiple Criteria Linear Programming Model”, International Journal of Data Warehousing and Mining, Vol. 7, No. 3, 88-101, 2011. (SCI).
125. Zhou, X., W. Jiang, Y. Shi and Y. Tian, “Credit Risk Evaluation with Kernel-based Affine Subspace Nearest Points Learning Method”, Expert Systems with Applications, Vol. 38, No. 4, 4272–4279, 2011. (SCI).
124. Nie, G., L. Zhang and Y. Shi, “Knowledge Push in Knowledge-Based Information System,” Journal of Computational Information System, Vol. 7, No. 4, 1342-1349, 2011. (EI).
123. Kwak, W., Y. Shi and Kou, G., “Bankruptcy Prediction for Korean Firms after the 1997 Financial Crisis: Using a Multiple Criteria Linear Programming Data Mining Approach,” DOI: 10.1007/s11156-011-0238-z, Review of Quantitative Finance and Accounting, Vol. 38, No. 4, 441-453, May 2012.
122. Ergu, D., G. Kou, Yi Peng, Yong Shi, Yu Shi, “The Analytic Hierarchy Process: Task Scheduling and Resource Allocation in Cloud Computing Environment,”Journal of Supercomputing,May 2011, DOI: 10.1007/s11227-011-0625-1. (SCI).
121.Ergu, D., G. Kou, Yong Shi and Yu Shi, “Analytic Network Process in Risk Assessment and Decision Analysis,” Computers & Operations Research, 2011.(SCI).
120. Jian, L., C. Wang, Y. Liu, S. Liang,W. Yi and Y. Shi,“Parallel data mining techniques on Graphics Processing Unit with Compute Unified Device Architecture(CUDA)”, The Journal of Supercomputing, Vol. 32, 3, June 2011:1-28. (SCI).
119. Li, A.,Y. Shi and J. He, “A Fuzzy linear programming-based classification method,” International Journal of Information Technology and Decision Making, Vol. 10, No. 6 (2011) 1161–1174. (SCI).
118. Chen, R., W. Chen, S. Yang, D. Wu, Y. Wang, Y. Tian and Y. Shi, “Rigorous Assessment and Integration of The Sequence and Structure Based Features to Predict Hot Spots”, BMC Bioinformatics, 2011, 12:311(http://www.biomedcentral.com/1471-2105/12/311). (SCI).
117. Ma, G., M. Shi and Y. Shi, “How Much Real Cost Has China Paid for Its EconomicGrowth, Sustainability Science, DOI 10.1007/s11625-011-0133-5, 2011.
116. Ergua, D., G. Kou, Y. Peng, and Y. Shi, “A Simple Method to Improve theConsistencyRatio of the Pair-wise Comparison Matrix in ANP,”European Journal of OperationalResearch, Vol.213, 246–259, 2011. (SCI).
115. Nie, G, W. Rowe, L. Zhang,Y. Tian and Y. Shi, “Credit Card Churn Forecasting by Logistic Regression and Decision Tree”, Expert Systems with Applications, Vol. 38, 15273–15285, 2011. (SCI).
114. Peng, Y., G. Wang, G. Kou and Y. Shi, “FAMCDM: A Fusion Approach of MCDM Methods to Rank Multiclass Classification Algorithms,” Omega: The International Journal of Management Science, Vol. 39, 677 – 689, 2011.(SCI, INSPEC).
113. Peng, Y., G. Kou, G. Wang, W. Wu and Y. Shi, “Ensemble of software defect predictors: an AHP-based evaluation method,” International Journal of Information Technology & Decision Making, Vol. 10, 187–206, 2011. (SCI).
112. Peng, Y., G. Wang, G. Kou and Y. Shi, “An Empirical Study of ClassificationAlgorithm Evaluation for Financial Risk Prediction, Applied Soft Computing, Vol. 11, 2906-2915, 2011. (SCI).
111. Ergua, D., G. Kou, Y. Peng, and Y. Shi and Y. Shi, “BIMM: A Bias Induced Matrix Model for Incomplete Reciprocal Pairwise Comparison Matrix,” DOI: 10.1002/mcda.472, Journal of Multi-Criteria Decision Analysis, 18(1) 101-113,2011.
110. Kou, G., W. Wu, Y. Peng, N. E. Yaw and Y. Shi, “A Dynamic Assessment Method for Urban Eco-environmental Quality Evaluation,” DOI: 10.1002/mcda.470, Journal of Multi-Criteria Decision Analysis, 18(1) 23-38,2011.
109. Zhang, P., X. Zhu, Y. Shi, L. Guo and X. Wu, “Robust Ensemble Learning for Mining Noisy Data Streams”, Decision Support Systems, Vol. 50, 2011. (SCI).
108. Liu, J., J. Li, W. Xu and Y. Shi, “A Weighted Lq Adaptive Least Squares Support Vector Machine Classifiers – Robust and Sparse Approximation”, Expert Systems with Applications, Vol. 38, 2253-2259, 2011. (SCI).
107. Chen, R., Z. Zhang, D. Wu, P. Zhang, X. Zhang, Y. Wang and Y. Shi, “Prediction of Protein Interaction Hot Spots Using Rough Set-Based Multiple Criteria Linear Programming”, Journal of Theoretical Biology, Vol. 269, No.1, 174-180, 2011. (SCI).
106. Zhou, X., W. Jiang, T. Tian and Y. Shi, “Kernel Subclass Convex Hull Sample Selection Method for SVM on Face Recognition”, Neurocomputing, Vol. 73, 2234-2246, 2010. (SCI).
105. Zhang,L., Y. Li, Y. Chen, X. Wang, J. Li, Y. F. Shi and Y. Shi, “Research on KnowledgeTransfer and sharing in the Implement of Manufacturing EPR,” Applied Mechanics and Materials, Vols. 26-28, 1040-1045. 2010. (EI).
104. Zhu, X. Q., X. D. Lin, P. Zhang and Y. Shi, “Active Learning from Stream Data Using Optimal Weight Classifier Ensemble”, IEEE Transactions on System, Man and Cybernetics -Part B, Vol. 40, 1607-1621, 2010. (SCI).
103. He, J., Y. Zhang, Y. Shi and G. Huang, “Domain-Driven Classification Based on Multiple Criteria and Multiple Constraint-Level Programming for Intelligent Credit Scoring”, IEEE Transactions on Knowledge & Data Engineering, Vol.22, 826-838, 2010. (SCI).
102. Z. Wang, Y. Liu, X. Liu and Y. Shi, “Robust State Estimation for Discrete-Time Stochastic Neural Networks with Probabilistic Measurement Delays”, Neurocomputing, Vol.74, 256–264, 2010. (SCI).
101. Zineddin B., Z. Wang, Y. Shi, Y. Li, M. Du and X. Liu, “A multi-view approach to cDNA micro-array analysis”, International Journal of Computational Biology and Drug Design,Vol. 3(2), 91-111, 2010.
100. Liu, Y., J. Li, W. K. Liao, A. Choudhary and Y. Shi, “High Utility Itemsets Mining,” International Journal of Information Technology and Decision Making, Vol. 9, No.6, 905-934, 2010. (SCI).
99. Zhang, Y. L. Zhang, Y. Liu and Y. Shi, “Mining Intelligent Knowledge from a Two-phase Association Rules Mining”, International Journal of Data Mining, Modelling and Management, Vol. 2(4), 2010. (Cabell).
98.Shi, Y., “Multiple Criteria Optimization based Data Mining Methods and Applications: A Systematic Survey”, Knowledge and Information Systems, 369-391，Vol. 24 (3), 2010.(SCI).
97. Zhang, P, X. Zhu, Z. Zhangand Y. Shi, “Multiple Criteria Programming for VIP Email Behavior Analysis”, International Journal of Web Intelligence & Agent Systems, Vol. 8, 69-78, 2010. (EI).
96. Zhang, L, J. Li, Y. Shiand X. Liu, “Foundations of Intelligent Knowledge Management”, The Journal of Human Systems Management, Vol. 28 (4), 145-161, 2009. (Cabell).
95. Zhang, W. R., J. H. Zhang, Y. Shiand S. S. Chen, “Bipolar Linear Algebra and YinYang-N-ElementCellular Networks for Equilibrium-Based Bio-systemSimulation and Regulation”, Journal of Biological Systems, Vol. 17 (4), 547-576, 2009. (SCI).
94. Nie, G, L. Zhang, Y. Liu, X. Zheng and Y. Shi, “Decision Analysis of Data Mining Project Based on Bayesian Risk”, Expert Systems with Applications, Vol. 36, 4589–4594, 2009. (SCI).
93. Zhang, D., Y. Shi, Y. Tian and M. Zhu, “A Class of Classification And Regression Methods By Multiobjective Programming”, Frontiers of Computer Science in China, Vol. 3, 192-204, 2009.
92. Li, X, L Zhang, P. Zhang and Y. Shi, “Problems and systematic Solutions in Data Quality”, International Journal of Services Science, vol. 2, No.1, pp. 53-69, 2009.
91. Zhang, J., Y. Shi and P. Zhang, “Several Multi-criteria Programming Methods for Classification”, Computers & Operations Research, Vol. 36, 823-836, 2009. (SCI).
90. Zhang, Z., G. Gao and Y. Shi, “A Rough Set-based Multiple Criteria Linear Programming Approach for the Medial Diagnosis and Prognosis”, Expert Systems with Applications, Vol. 36, 8932-8937, 2009. (SCI).
89. Kou, G, Y. Peng, Z. Chen and Y. Shi, “Multiple criteria mathematical programming for multi-class classification and application in network intrusion detection”, Information Sciences, Vol. 179, Issue 4, 371–381, 2009. (SCI, SSCI).
88. Shi, Y, Y. Tian, X. Chen and P. Zhang, “Regularized Multiple Criteria Linear Programs forClassification”, Science in China Series F: Information Sciences, Vol. 52, 1812-1820, 2009. (SCI).
87. Zhang, Z, Y. Shi and Y. Tian, “An effective classification approach based on fuzzy set and multiple criteria linear programming”, Journal of Data Analysis, Vol. 4, No. 1, 2009.
86．Yan, N., Z. Chen, Y. Shi and R. Liu “An Optimization-Based Classification Approach with the Non-additive Measure”, International Journal of Operations and Quantitative Management, Vol. 14, 285-296, 2008.
85. Zhang, P., Y. Tian, Z. Zhang, X. Li and Y. Shi“Supportive instances for Regularized Multiple Criteria Linear Programming Classification”, International Journal of Operations and Quantitative Management, Vol. 14, 249-263, 2008.
84. Zhang, Z., P. Zhang and Y. Shi, “A Rough Set-based Multiple Criteria LinearProgramming Approach for Improving Classification Performance”, International Journal of Operations and Quantitative Management, Vol. 14, 211-235, 2008.
83. Peng, Y., Kou, G., Shi, Y., and Chen, Z.，A Descriptive Framework for the Field of Data Mining and Knowledge Discovery, International Journal of Information Technology and Decision Making, Vol. 7, No.4, 639-682, 2008. (SCI).
82. Zhang, L., J. Li, X. Zheng, X. Li and Y. Shi, “Study on a Process-Oriented Knowledge Management Model,” International Journal of Knowledge and Systems Sciences,Vol. 5, No.1, 2008.
81. Zheng, X., L. Zhang, G. Nie and Y. Shi, “A Way to Accelerate Knowledge Management: from the Perspective of Knowledge Potential,” Journal of Service Science and Management Vol. 1, 226-232, 2008.
80. Zhang P., Z. Zhang, A. Li, Y. Shi, “Global and Local (Glocal) Bagging Approach forClassifying Noisy Dataset”, International Journal of Software and Informatics, Vol.2, No.2, 181-197, 2008.
79. Li J., L. L. Zhang and Y. Shi “Research on Evaluation Model of Organizational Knowledge Assets,” Journal of Information & Knowledge Management, Vol. 7, No. 1 1–8, 2008.
78. Peng, Y., G. Kou, Y. Shi, and Z. Chen “A Multi-Criteria Convex Quadratic Programming Model for Credit Data Analysis,” Decision Support Systems, Vol. 44, 1016-1030, 2008. (SCI).
77. Liu, R. and Y. Shi “Sampling Based Succinct Matrix Approximation,” Statistics and Probability Letters, Vol. 78, 1138-1147, 2008. (SCI).
76. Li, A., Y. Shiand J. He, “MCLP-based Methods for Improving‘Bad’ Catching Rate in Credit Cardholder Behavior Analysis,”Applied Soft Computing, 8(3), 1259-1265, 2008. (SCI).
75. Zhang, Y., L. Chen, Z. Zhou and Y. Shi, “A Geometrical Method on Multidimensional Dynamic Credit Evaluation”,International Journal of Information Technology and Decision Making, Vol. 7, No. 1, 103-114, 2008. (SCI).
74. Liu, G., Z. Zhou and Y. Shi, “A Multi-Dimensional Forward Selection Method for Firms’ Credit Sale,” Computers & Mathematics with Applications, Vol. 54, 1228-1233, 2007. (SCI).
73. He, J., X. Chen, Y. Shi and A. Li “Dynamic Computable General Equilibrium Model and Sensitivity Analysis for Shadow Price of Water Resource in China,” Water Resource Management, 21(9), 1517-1533, 2007. (SCI).
72. Hu, J., N. Zhong and Y. Shi, “Developing Mining-Grid Centric E-Finance Portals for Risk Management and Decision Making,” International Journal of Pattern Recognition and Artificial Intelligence, Vol. 21, No. 4, 639–658, 2007.
71. Shi, Y., X. Zhang, J. Wan, G. Kou, Y. Peng, and Y. Guo, “Comparison study of two kernel-based learning algorithmsfor predicting the distance range between antibodyinterface residues and antigen surface”, International Journal of Computer Mathematics, Vol.84, 690-707, 2007. (SCI).
70.Shi, Y., X. Zhang, J. Wan, Y.Wang, W.Ying, Z. Cao, Y. Guo, “Predicting theDistance between Antibody’s Interface Residue And Antigen To Recognize Antigen Types By Support Vector Machine”, Neural Computing & Applications, Vol.16, 481-490,2007. (SCI).
69. Cheng S., R. Dai, W. Xu, Y. Shi, “Research on Data Mining and KnowledgeManagement and Its Applications in China’s Economic Development: Significance and Trend”,International Journal of Information Technology and Decision Making, Vol. 5, No. 4, 585–596, 2006. (SCI).
68. Zhang, L., Y. Shi, and X. Yang, “Association-Rule Knowledge Discovery by Using A Fuzzy Mining Approach,” International Journal of Data Mining and Business Intelligence, Vol. 1, 417 – 429, 2006.
67. Kwak, W., Y. Shi, S. Eldridge and G. Kou, “Bankruptcy Prediction for Japanese Firms: Using Multiple Criteria Linear Programming Data Mining Approach,” International Journal of Data Mining and Business Intelligence, Vol. 1, 401-416, 2006.
66. Yang, H., Y. Li and Y. Shi, “Bank Regulating System of Hong Kong Monetary Authority and Its Implication to China,” Management Review, Vol. 18, 3-8, 2006. (in Chinese).
65. Kwak, W., Y. Shi and J. Cheh, “Firm Bankruptcy Prediction Using Multiple Criteria Linear Programming Data Mining Approach,” Advances in Financial Planning and Forecasting, Vol. 2, 27-49, 2006.
64. He, J., X. Chen and Y. Shi, “A Dynamic Approach to Calculate Shadow Prices of Water Resources for Nine Major Rivers in China,” Journal of Systems Science and Complexity, Vol. 19, 76-87, 2006. (INSPEC).
63. Shi, Y., Y. Peng, G. Kou and Z. Chen, “Classifying Credit Card Accounts for Business Intelligence and Decision Making: A Multiple-Criteria Quadratic Programming Approach,” International Journal of Information Technology and Decision Making, Vol. 4, 581-600, 2005. (SCI).
62. Zhou, Z., T. Mou and Y. Shi, “The Mathematical Structure of Credit Evaluation,” Far East Journal of Applied Mathematics, Vol. 20, 113-119, 2005.(MathSci).
61. Shi, Y., H. Yang and L. Zhang, “Promoting China’s National Competitiveness by Using Knowledge Management and Data Mining,” China Soft Science, Vol. 176, 46-51, 2005. (in Chinese).
60. Shi, Y., J. He, L. Wang and W. Fan, “Computer-based Algorithms for Multiple Criteria and Multiple Constraint Levels Integer Linear Programming,” Computers & Mathematics with Applications, Vol. 49, 903-921, 2005. (SCI, EI, INSPEC, MathSci).
59. Kou, G., Y. Peng, Y. Shi, M. Wise and W. Xu, "Discovering Credit Cardholders’Behavior by Multiple Criteria Linear Programming", Annals of Operations Research, Vol.135, 261-274, 2005. (SCI,ISTP, INSPEC, MathSic).
58. He, J., X. Liu, Y. Shi, W. Xu and N. Yan "Classifications of Credit Cardholder Behavior by using Fuzzy Linear Programming", International Journal of Information Technology and Decision Making, Vol. 3, 633-650, 2004. (SCI).
57. Zheng, J., W. Zhuang, N. Yan, G. Kou, D. Erichsen, C. McNally, H. Peng, A. Cheloha, C.Shi, and Y. Shi, "Classification of HIV-1 Mediated NeuronalDendritic and Synaptic Damage Using Multiple Criteria Linear Programming," Neuroinformatics, Vol. 2, 303-326, 2004.(SCI).
56. Tang, X., Z.Zhou, C. Zhang and Y. Shi, "Multi-Objective Constrained Nonlinear Optimization: An ODE Approach," Information – International Inter-discipline Journal, Vol. 7, 487-495, 2004.(MathSic).
55. Kwak, W., Y. Shi, and K. Jung, “Human Resource Allocation for A CPA Firm: A FuzzySet Approach”, Review of Quantitative Finance and Accounting, Vol. 20, 277-290, 2003.
54. Kou, G., X. Liu, Y. Peng, Y. Shi, M. Wise and W. Xu, “Multiple Criteria LinearProgramming to Data Mining: Models, Algorithm Designs and Software Developments”Optimization Methods and Software, Vol. 18, 453-473, 2003. (SCI, EI, ISTP, MathSci).
53. Tang, X., Z. Zhou and Y. Shi, “The Variable Weighted Functions of CombinedForecasting”, ComputersandMathematics with Applications, Vol. 45, 723-730, 2003.(SCI, EI, INSPEC, MathSci).
52. Tang, X., Z. Zhou and Y. Shi, “The Errors Bounds of Combined Forecasting”, Mathematical and Computer Modelling, Vol. 36, 997-1005, 2002.(SCI,MathSci).
51. Tang, X., Z. Zhou and Y. Shi, “Errors Bound under -orthogonal in Variable Weight Combined Forecasting”,Information – International Inter-discipline Journal, Vol. 5, 403-416, 2002.(MathSci).
50. Zhong,Y. and Y.Shi, “Duality in Fuzzy Multi-criteria and Multi-constraint Level Linear Programming: A Parametric Approach”,Fuzzy Sets and Systems, Vol. 132, 335-346, 2002. (SCI, EI, INSPEC, MathSci).
49. Peng, Y., Y. Shi and W. Xu, “Classification for Three-group of Credit Cardholders’Behavior Via A Multiple Criteria Approach”, Advanced Modeling and Optimization (Online Journal), Vol. 4, 39-56, 2002.
48. Shi, Y, Y. Peng, W. Xu and X. Tang, “Data Mining via Multiple Criteria LinearProgramming: Applications in Credit Card Portfolio Management”, International Journal of Information Technology and Decision Making, Vol. 1, 131-151, 2002. (SCI,INSPEC).
47. Shi, Y., W. Kwak, H. Lee and C. F. Lee “Capital Budgeting with Multiple Criteria and Multiple Decision Makers: A Fuzzy Approach”,Journal of Advanced Computational Intelligence, Vol. 5, 139-148, 2001.
46. Li, J. and Y. Shi, “An Integer Linear Programming with Multi-Criteria and Multi-Constraint
Levels: A Branch-and-Partition Algorithm”, International Transactions in Operational Research, Vol. 8, 497-509, 2001.(INSPEC, MathSci).
45. Li, J., Y. Shiand J. Zhao, “Time-Cost Trade-off in A Transportation Problem with Multi-Constraint Levels”,OR Transactions, Vol. 5, 11-20, 2001.
44. Lee, H., Y. Shi, S. N. Nazem, S. Y. Kang, T. H. Park and M. H. Sohn, “Multicriteria Hub
Decision Making for Rural Area Telecommunication Networks”,European Journal of Operational Research, Vol. 133, 483-495, 2001. (SCI, EI, INSPEC).
43. Zhong, Y. and Y. Shi, “An Interior-Point Approach for Solving MC2 Linear Programming”,
Mathematical & Computer Modelling, Vol. 34, 411-422, 2001.(SCI, INSPEC, MathSci).
42. Shi, Y., “Humancasting: A Fundamental Method to Overcome User Information Overload,” Information – International Inter-discipline Journal, Vol. 3, 127-143, 2000.
41. Li, J. and Y. Shi, " A Dynamic Transportation Model with Multiple Criteria and MultipleConstraint Levels," Mathematical & Computer Modelling, Vol. 32, 1193-1208, 2000. (SCI, INSPEC, MathSci).
40. Shi, Y., "Optimal System Design with Multi-Decision Makers and Possible Debt: A Multi-Criteria De Novo Approach," Operations Research, Vol. 47, 723-729, 1999.(SCI, EI, INSPEC).
39. Zhou, Z., Y. Shi and X Hao, "An MC2 Linear Programming Approach to CombinedForecasting," Mathematical and Computer Modelling, Vol. 29, 97-103, 1999.(SCI, INSPEC, MathSci).
38. Lee, H., J. Lee, S. M. Nazem, Y. Shi and J. D. Stolen, "Managing User Performance for A Corporate Network", Information and Management, Vol. 35, 251-263, 1999. (SCI, EI, INSPEC, MathSci).
37. Shi, Y., "A Review of MC2 Linear Programming: Theory and Applications," International Journal of Operations and Quantitative Management, Vol. 5, No. 2, 137-150, 1998.
36. Shi, Y., "Finding Dual Flexible Contingency Plans for Optimal Generalized Linear Systems," International Transactions inOperations Research, Vol.5, No. 4,
303-315, 1998.(INSPEC).
35. Xiao, W., Z. Liu, M. Jiang and Y. Shi, "Multiobjective Linear Programming Model on Injection Oilfield Recovery System," Computers & Mathematics withApplications, Vol.36, 127-135, 1998.(SCI, EI, INSPEC).
34. Shi, Y., "Optimal System Design with MC2 Linear Programming: A Dual Contingency Plan Approach," European Journal of Operational Research, Vol. 107, 692-709, 1998. (SCI, EI, ISTP, INSPEC).
33. Shi, Y., W. Kwak and H. Lee, "Optimal Trade-offs of Multiple Factors in Transfer Pricing Problems," Multi-Criteria Decision Analysis, Vol. 7, 98-108, 1998.
32. Zhou, Z. and Y. Shi, "A Convergence of ODE Method in Constrained Optimization," Journal of Mathematical Analysis and Applications, Vol. 218, 297-307, 1998.(SCI, EI, MathSci).
31. Zhou, Z. and Y. Shi, "An ODE Method of Solving the Nonlinear Programming," Computers & Mathematics with Applications, Vol. 34, 97-102, 1997.(SCI, EI, INSPEC).
30. Shi, Y.and H. Lee, "A Binary Integer Linear Program with Multiple Criteria and Multiple Constraint Levels," Computers and Operations Research, Vol. 24, 259-273, 1997. (SCI, EI, INSPEC).
29. Lee, H., Y. Shi and S. N. Nazem, "Supporting Rural Telecommunications: A Compromise Solutions Approach," Annals of Operations Research, Vol. 68, 33-45, 1996.(SCI, EI, INSPEG).
28. Lee, G., Y. Liu, K. Wu and Y. Shi, "Supporting Economic Reform of Chinese Petroleum Industry: A Dynamic Decision-Making Model," Engineering Economist, Vol. 42, 1-18, 1996. (EI, INSPEC).
27. Shi, Y. and C. Haase, "Optimal Trade-offs of Aggregate Production Planning with Multi-Criteria and Multi-Capacity-Demand Levels," International Journal of Operations and Quantitative Management, Vol. 2, 127-143, 1996.
26. Kwak, W., Y. Shi, H. Lee and C. F. Lee, "Capital Budgeting with Multiple Criteria and Multiple Decision Makers," Review of Quantitative Finance and Accounting, Vol. 7, 97-112, 1996.
25. Nazem, S. M., Y. H. Liu, H. Lee and Y. Shi, "Implementing Telecommunication Infrastructure: A Rural America Case," Telematics and Informatics, Vol. 13, 23-31, 1996.(EI, INSPEC).
24. Shi, Y., P. L. Yu and D. Zhang. "Generalized Optimal Designs and Contingency Plans in Linear Systems," European Journal of Operational Research, Vol. 89, 618-641, 1996.(SCI, EI, INSPEC).
23. Shi, Y., P. Specht, J. Stolen and F. VanWetering, "A Consensus Ranking for Information System Requirements," Information Management &Computer Security, Vol. 4, 10-18,1996.(INSPEC).
22. Liu, Y. and Y. Shi, "A Weighted Fuzzy Similar Method for Ranking A Set of Alternatives with Multiple Criteria," Mathematical Education in Science and Technology, Vol. 26, No. 4, 545-552, 1995.
21. Liu, Y., Y. Shi and Y. H. Liu "Duality of Fuzzy MC2 Linear Programming: A Constructive Approach," Journal of Mathematical Analysis and Applications, Vol. 194, 389-413, 1995. (SCI, EI, MathSci).
20. Shi, Y., "Constructing Flexible Dual Contingency Plans for Optimal Linear Designs with Multiple Criteria," Journal of Mathematical Analysis and Applications, Vol. 191, 277-304, 1995. (SCI, EI, MathSci).
19. Shi, Y., "A Transportation Model with Multiple Criteria and Multiple Constraint Levels," Mathematical and Computer Modelling, Vol. 21, No. 4, 13-28, 1995.(SCI, EI, INSPEC).
18. Shi, Y., "Studies on Optimum-path Ratios in DE NOVO Programming Problems," Computers and Mathematics with Applications, Vol. 29, No. 5, 43-50, 1995.(SCI, EI, INSPEC, MathSci).
17. Lin, S. L. and Y. Shi, "Welfare Effects of Capital Taxation in A Growing Economy with Deficit Finance," Public Finance, Vol. 49, No. 2, 391-408, 1994.
16. Shi, Y. and Z. He, "Dual Contingency Plans in Optimal Linear Generalized Designs," Systems Science, Vol. 25, No. 8, 1267-1292, 1994.(SCI, INSPEC, MathSci).
15. Lee, H., S. M. Nazem and Y. Shi, "Designing Rural Area Telecommunication Networks via Hub Cities," Omega: The International Journal of Management Science, Vol. 22, No. 3, 305-314, 1994.(SCI, INSPEC).
14. Liu, Y. H. and Y. Shi, "A Fuzzy Programming Approach for Solving A Multiple Criteria and Multiple Constraint Level Programming Problem," Fuzzy Sets and Systems, Vol. 65, 117-124, 1994. (SCI, EI, INSPEC, MathSci).
13. Shi, Y., P. L. Yu, C. Zhang and D. Zhang, "A Computer-Aided System for Linear Production Designs," Decision Support Systems, Vol. 12, Sept., 127-149, 1994. (SCI, EI, INSPEC).
12. Shi, Y., P. L. Yu and D. Zhang, "Generating New Designs Using Union Operations," Computers and Mathematics with Applications, Vol. 27, No. 12, 105-117, 1994. (SCI, MathSic).
11. Shi, Y., P. L. Yu and D. Zhang, "Eliminating Permanently Dominated Opportunities in Multiple-Criteria and Multiple-Constraint Level Linear Programming," Journal of Mathematical Analysis and Applications, Vol.183, No.3, 685-705, 1994. (SCI, EI, INSPEC, MathSci).
10. Lee, H., Y. Shi and J. D. Stolen, "Allocating Data Files over A Wide Area Network: Goal Setting and Compromise Design," Information and Management, Vol. 26, 85-93, 1994. (SCI, INSPEC).
9. Shi, Y. and Y. H. Liu, "Fuzzy Potential Solutions in Multi-Criteria and Multi-Constraint Levels Linear Programming Problems," Fuzzy Sets and Systems, Vol. 60, No. 2, 163-179, 1993. (SCI, EI, INSPEC, MathSci).
8. Shi, Y. and D. Zhang, "Flexible Contingency Plans in Optimal Linear Designs," Mathematical and Computer Modelling, Vol. 17, No. 7, 13-28, 1993.(SCI, INSPEC, MathSci).
7. Gyetvan, F. and Y. Shi, "Weak Duality Theorem and Complementary Slackness Theorem for Linear Matrix Programming Problems," Operations Research Letters, Vol. 11, No. 4, 249-253, 1992. (SCI, EI, INSPEC, MathSci).
6. Shi, Y. and P. L. Yu, "Selecting Optimal Linear Production Systems in Multiple Criteria Environments," Computers and Operations Research, Vol. 19, No. 7, 585-608, 1992. (SCI, EI, INSPEC).
5. Lee, Y. R., Y. Shi and P. L. Yu, "Linear Optimal Designs and Optimal Contingency Plans," Management Science, Vol. 36, No. 9, 1106-1119, 1990. (SSCI, EI, INSPEC).
4. Shi, Y. and P.L. Yu, "Habitual Domain Analysis for Effective Decision Making," Asia-Pacific Journal of Operational Research, Vol. 4, No. 2, 131-150, 1987. (INSPEC).
3. Zhou, L. X., Y. Shi and S. Q. Wang, "The Method of Fuzzy Mathematics in Analysis of Reservoir Porous Structure," Journal of Petroleum Exploration and Development, Vol. 11, No. 5, 56-65, 1984. (in Chinese).
2. Shi, Y., "Convergence Theorem of Fuzzy Integral of Type II," Journal of Southwest Petroleum Institute, Vol. 7, No. 4, 74-81, 1981. (in Chinese).
1. Shi, Y., "Another Isomorphic Theorem on Fuzzy Subgroups and Fuzzy Series of Invariant Subgroups," Journal of Southwest Petroleum Institute, Vol. 6, No. 3, 79-82, 1981. (in Chinese).
Refereed Book Articles (SCI: 21, EI: 93, ISTP: 86, INSPEC: 14, MathSci: 4):
180. Y. Shi, W. An, Y. Qu, “A Text Mining-Based Decision Support and Case File Classification Management System for Prosecution,” in La Digitalizzazione dell’ Amministrazione Finanziaria tra Contrasto all’ Evasione e Tutela dei Diritti del Contribuente (Vol. IV), Farri, F. and A. Marcheselli (Eds.), Milan: Giuffré, 2025, pp. 221–254.
179. Feng J, Shi Y. “A Bibliometric Studies of Pre-trained Model and Fine-tune Method,”Procedia Computer Science, 2025, 266: 1295-1304.(EI).
178. Deng, Xiannian, and Yong Shi. “A Study on the Causes and Regulation of Data Market Failure”, Procedia Computer Science 266 (2025): 1220-1225.(EI).
177. E. Eremina, Y. Shi, “Macroprudential policy in retail lending: Concept and results–a case study of the Bank of Russia,” Procedia Computer Science, 242, 1331-1338, 2024.
176. M. Li, Y. Qu, Y. Shi, “Latest Technologies on Dataset Distillation: A Survey,” Procedia Computer Science, 242, 1112-1117, 2024.
175. F. G. Filip, Y. Shi, P. Pocatilu, C. E. Ciurea, J. Li, J. M. Tien, D. Berg, “Frontiers of Artificial Intelligent and Quantitative Management: Preface for ITQM 2024,” Procedia Computer Science, 242, 1-8, 2024.
174. L. Zheng, P. Quan, Y. Shi, L. Niu, “A Brief Survey of Distribution Robust Graph Neural Networks,” Procedia Computer Science, 242, 1281-1286, 2024.
173. R. Xu, Y. Shi, Z. Qi, “Image Orientation Estimation Based On Deep Learning-A Survey,” Procedia Computer Science, 242, 1193-1197, 2024.
172. J. Xue, J. Liu, Y. Shi, “Overview of Essential Components in deep learning reference-based super resolution methods,” Procedia Computer Science, 242, 1243-1248, 2024.
171. Y. Shi, S. Peng, A. Yu, K. Guo, “Research on Liquidity Measurement and Influencing Factors of China Carbon Emission Allocation Trading Market,” Procedia Computer Science, 221, 1448-1457, 2023.
170. J. S. Raj, Y. Shi, D. Pelusi, V. E. Balas, “Intelligent Sustainable Systems,” Department of Computer Science, City University of Hong Kong, 2023.
169. J. Yang, M. Lyu, Z. Qi, Y. Tian, Y. Shi, “Deep feature inpainting for unsupervised visual anomaly detection,” Procedia Computer Science, 221, 901-911, 2023.
168. J. Yang, M. Lyu, Z. Qi, Y. Shi, “Deep Learning Based Image Quality Assessment: A Survey,” Procedia Computer Science, 221, 1000-1005, 2023.
167. Y. Wang, J. Wu, Y. Shi, “Stock index prediction using global market indices: A Granger causality-based graph representation learning method,” Procedia Computer Science, 221, 797-804, 2023.
166. Y. Qu, X. Xue, Y. Shi, “Graph classification based fault detection in nuclear power plants with graph formulation,” Procedia Computer Science, 221, 657-663, 2023.
165. Y. Shi, F. G. Filip, J. He, J. Li, G. Kou, J. M. Tien, D. Berg, “Global Collaboration to Enhance Information Technology & Quantitative Management: Preface for ITQM 2023,” Procedia Computer Science, 221, xv-xxii, 2023.
164. T. Yao, Y. Shi, M. Chen, “Review and research frontier analysis of low carbon economy–Based on bibliometric methods,” Procedia Computer Science, 221, 1292-1301, 2023.
163. Tang A., Quan P., Niu L., Shi Y., A Survey of Sparse Regularization Based Compression Methods, Procedia Computer Science, 2022, 199, 703–709.
162. Yang J., Xu R., Qi Z., Shi Y., Visual Anomaly Detection: A Systematic Review, Procedia Computer Science, 2022, 199, 471-478.
161. Shi Y., Quan P., Big Data Analysis: Theory and Applications, In: Lirkov I., Margenov S. (eds) Large-Scale Scientific Computing, LSSC 2019, Lecture Notes in Computer Science, Vol 11958, 15-27, Springer.
160. Qu Yi, Quan Pei, Lei Minglong, Shi Y., Review of bankruptcy prediction using machine learning and deep learning techniques[C]// Procedia computer science, 2019, 162, 895-899.
159. Shi Y., Xiao Yang and NiuLingfeng. A Brief Survey of Relation Extraction Based on Distant Supervision, International Conference on Computational Science, 2019, 293-303.
158. Quan P., Shi Y., Lei M., Leng J., Zhang T., Niu L., A Brief Review of Receptive Fields in Graph Convolutional Networks, ACM International Conference on Web Intelligence(WI), 2019, 106–110.
157. Li Biao, Shi Y., Li Sujuan, Wang, B., Qi Z., Liu J, Novel Texture Generation Super Resolution Model, Procedia computer science, 2019, 162, 924-931.
156. Qu Y, Shi Y., Guo K, et al. Has “Intelligent Manufacturing” Promoted the Productivity of Manufacturing Sector?--Evidence from China’s Listed Firms, Procedia computer science, 2018, 139: 299-305.
155. Quan P, Liu Y, Shi Y., et al. A Novel Data Mining Approach Towards Human Resource Performance Appraisal, International Conference on Computational Science. Springer, Cham, 2018: 476-488.
154. Quan P, Shi Y., Niu L, et al. Automatic Chinese Multiple-Choice Question Generation for Human Resource Performance Appraisal, Procedia computer science, 2018, 139: 165-172.
153. Shi Y., Zheng Y, Guo K, Li W. and Zhu L. Word Similarity Fails in Multiple Sense Word Embedding, International Conference on Computational Science. Springer, Cham, 2018: 489-498.
152. Lei M, Shi Y., Li P, et al. Deep Streaming Graph Representations, International Conference on Computational Science. Springer, Cham, 2018: 512-518.
151. Cui L, Chen Z, Shi Y., et al. Multi-View Fusion Through Cross-Modal Retrieval, 2018, 25th IEEE International Conference on Image Processing (ICIP). IEEE, 2018: 1977-1981.
150. Cui L, Chen Z, Shi Y., et al. Multi-view Collective Tensor Decomposition for Cross-modal Hashing[C]//Proceedings of the 2018 ACM on International Conference on Multimedia Retrieval. ACM, 2018: 73-81.
149. Liu, F., Shi, Y., Li, P., Analysis of the Relation between Artificial Intelligence and the Internet from the Perspective of Brain Science, Procedia Computer Science:Proceedings of The Fifth International Conference on Information Technology and Quantitative Management (ITQM 2017), vol. 122, pp. 377-383.
148. Liu, F., Shi, Y., Najjar, L., Application of Design of Experiment Method for Sports Results Prediction, Procedia Computer Science: Proceedings of The Fifth International Conference on Information Technology and Quantitative Management (ITQM 2017), vol. 122, pp. 720-726.
147. Zheng, Y., Guo, K., Shi, Y., Zhu, L., Li, W., Enhanced Word Embedding With Multiple Prototypes, Proceedings of International Conference on Industrial Economics System and Industrial Security Engineering (IEIS 2017), vol. IEEE Conferences (2017), pp. 1-5.
146. Chang, X. and Y. Shi, The Econometric Study on Effects of Chinese Economic Growth of Human Capital, Procedia Computer Science, 91, 1096-1105, 2016. (ISTP).
145. Li, T.,Y. Peng,Y. Shi and G. Kou, Study on Multi-agent Based Simulation of Team Machine Learning, Procedia Computer Science, 91, 847-854, 2016. (ISTP).
144. Liu, F., X. Li, Y. Shi, Scientific Breakthrough Study of Extenics, Procedia Computer Science, 91, 526-531, 2016. (ISTP).
143. R. Ren, L. Zhang, L. Cui, B. Deng, and Y. Shi, Personalized Financial News Recommendation Algorithm Based on Ontology, Procedia Computer Science, 55, 843-851, 2015. (ISTP).
142. B. Wang, Y. Shi, Z. Yang, X. Ju, An Algebra Description for Hard Clustering, Procedia Computer Science, 62-69, 2015. (ISTP).
141. L. Cui, Z. Qi, Z. Chen, F. Meng, and Y. Shi, Pavement Distress Detection Using Random Decision Forests, Data Science, Springer International Publishing, 95-102, 2015. (ISTP).
140. F. Meng, Z. Qi, L. Cui, Z. Chen, and Y. Shi, Supervised Object Boundary Detection Based on Structured Forests, Data Science, Springer International Publishing, 87-94, 2015. (ISTP).
139. Z. Chen, Z. Qi, F. Meng, L. Cui, andY. Shi, Image Segmentation via Improving Clustering Algorithms with Density and Distance,Procedia Computer Science,55, 1015-1022, 2015. (ISTP).
138. Z. Yang, Y. Shi, and B. Wang, Search Engine Marketing, Financing Ability and Firm Performance in E-commerce, Procedia Computer Science, 55: 1106-1112, 2015. (ISTP).
137. Yang Z. F., Y. Shi, B. Wang, H. Yan, Website Quality and Profitability Evaluation in E-Commerce Firms Using Two-stage DEA Model, Procedia Computer Science, 30: 04-13, 2014. (ISTP).
136. Feng Liu, Yong Shi. Research on the Neurology-based Internet Architecture, Procedia Computer Science, 30: 34-38, 2014. (ISTP).
135. Feng Liu, Yong Shi. The Search Engine IQ Test based on the Internet IQ Evaluation Algorithm, Procedia Computer Science, 31: 1066-1073, 2014. (ISTP).
134. Limeng Cui, Yong Shi. A Method Based on One-Class SVM for News Recommendation, Procedia Computer Science, 31: 281-290, 2014. (ISTP).
133. Yibing Chen, Cheng-Few Lee, Yong Shi, How the Market Judges Bank Risk: An Empirical Comparison between US and China, Procedia Computer Science, Volume 30, 2014, Pages 14-23.(ISTP).
132. Yibing Chen, Xianhua Wei, Lingling Zhang and Yong Shi, Sectoral Diversification and the Banks’ Return and Risk: Evidence from Chinese Listed Commercial Banks, Procedia Computer Science: ICCS 2013, 18 (2013):1737-1746. (EI).
131. Fan Wang, Peng Zhang, Yanmin Shang and Yong Shi, The Application of Multiple Criteria Linear Programming in Advertisement Clicking Events Prediction, Procedia Computer Science: ICCS 2013, 18(2013):1720-1729. (EI).
130. LingfengNiu, Xi Zhao and Yong Shi, A Simple Regularized Multiple Criteria Linear Programs for Binary Classification, Procedia Computer Science: ICCS 2013, 18(2013):1690-1699. (EI).
129. Zhiquan Qi, Yingjie Tian, Yong Shi and Xiaodan Yu, Cost-Sensitive Support Vector Machine for Semi-Supervised Learning, Procedia Computer Science: ICCS 2013, 18(2013):1684-1689. (EI).
128. Xi Zhao, Wei Deng and Yong Shi, Feature Selection with Attributes Clustering by Maximal Information Coefficient, Procedia Computer Science: ITQM 2013, 17(2013):70-79. (EI).
127. Chengcheng Liu and Yong Shi, Scene Image Mosaic Based on Three Freedom Degree, Procedia Computer Science: ITQM 2013, 17(2013):62-69. (EI).
126. Emma Haddi, Xiaohui Liu and Yong Shi, The Role of Text Pre-processing in Sentiment Analysis, Procedia Computer Science: ITQM 2013, 17(2013):26-32. (EI).
125. Yingjie Tian, Xuchan Ju, Zhiquan Qi, Yong Shi, Efficient Sparse Least Squares Support Vector Machines for Pattern Classification. 2012 9th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD2012): 714-718. (EI).
124. Gang Lv, BuleiYu, Zhangqi Chen, Zongfang Zhou, Yong Shi,The Analysis of Peasant Household's Credit Behavior, Procedia Computer Science 9(2012):1234-1239. (EI).
123. Zhiquan Qi, Yingjie Tian, Yong Shi, Regularized Multiple Criteria Linear Programming via Linear Programming. Procedia Computer Science 9(2012):1234-1239. (EI).
122. LingfengNiu, Jianmin Wu, Yong Shi, Entity Disambiguation with Textual and Connection Information, Procedia Computer Science 9(2012):1249-1255. (EI).
121. Yi Peng, Yong Zhang, Gang Kou, Jun Li, Yong Shi, Multicriteria Decision Making Approach for Cluster Validation, Procedia Computer Science 9(2012):1283-1291. (EI).
120. Lingling Zhang, Caifeng Hu, Quan Chen, Yibing Chen, Yong Shi, Domain Knowledge Based Personalized Recommendation Model and Its Application in Cross-selling, Procedia Computer Science 9(2012):1314-1323. (EI).
119. Le Yang, Zhongbin Ouyang, Yong Shi, A Modified Clustering Method Based on Self-Organizing Maps and Its Applications, Procedia Computer Science 9(2012):1371-1379. (EI).
118. Fang Wang, Yong Shi, An improvement of choosing map-join candidates in Hive, Procedia Computer Science 9(2012):2012-2015. (EI).
117. Zhiquan Qi, Yingjie Tian, Yong Shi, Rgularized Multiple Criteria Second Order Cone Programming Formulations, KDD(DMIKM), 2012. (EI).
116. Zhiquan Qi, Yingjie Tian, Yong Shi, A Simple and Fast Multi-Instance Classification via Support Vector Machine, WIC, 2012. (EI).
115. Ye Wang, CaimingZhang , Xinyang Zhang, GuanghuaChen,Yong Shi, Empirical Research on the Total Factor Productivity of ChineseSoftware Companies, The Workshop of the 2012 IEEE/WIC/ACM InternationalConference on Web Intelligence, 2012. (EI).
114. L. Niu, J. Wu, Y. Shi, “Entity Resolution with Attribute and Connection Graph”, icdmw, pp.267-271, 2011 IEEE 11th International Conference on Data Mining Workshops, 2011.
113. W. Suphamitmongkol, G. Nie, R. Liu, Y. Shi, “Classification for Orange Varieties Using Near Infrared Spectroscopy”, icdmw, pp.280-285, 2011 IEEE 11th International Conference on Data Mining Workshops, 2011.
112. Wang Z., N. Yan, J. Chu and Y. Shi, A nonlinear multiregression model based on the Choquet integral for analyzing the course records, ECICE 2012.
111. L.-F. Niu and Y. Shi, Second-order Mining for Active Collaborative Filtering, Procedia Computer Science, 4: 1726-1734, 2011. (EI).
110. L.-F. Niu and Y. Shi, MSSVM: A Modular Solver for Support Vector Machines, Proceeding of the IEEE/ WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology, 225-228, 2011. (EI).
109. Wang Z., R. Yang, Y. Shi, A new nonlinear classification model based on cross-oriented Choquet integrals, IEEE, 2011, 176-181. (EI).
108. L-F. Niu and Y. Shi, MSSVM: A Modular Solver for Support Vector Machines, Proceedings of 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology. (EI).
107. Y. Chen, L. Zhang, J. Li and Y. Shi, “Domain Driven Two-phase Feature Selection Method Based on Bhattacharyya Distance and Kernel Distance Measurements,” The 2011 IEEE/WIC/ACM International Conference on Web Intelligence, Lyon, France, Issue Date: 22-27 Aug. 2011: 217 – 220. (EI).
106. Y. Chen, L. Zhang and Y. Shi, Post Mining of Multiple Criteria Linear Programming Classification Model in Credit Card Churning Management. The 11th IEEE International Conference on Data Mining, Vancouver, Canada, December 11-14, 2011. (EI).
105. Nie, G., L. Zhang, Y. Zhang, W. Deng, and Y. Shi, “Find Intelligent Knowledge by Second-Order Mining: Three Cases from China,”2010 IEEE International Conference on Data Mining Workshops, Dec. 14-17, 1189-1195, 2010. (ISTP).
104. Zhou, X. and Y. Shi, “Subspace Distance-Based Sampling Method for SVM,”2010 IEEE International Conference on Data Mining Workshops, Dec. 14-17, 1289-1296, 2010. (ISTP).
103. Niu, L. and Y. Shi, “Semi-supervised PLSA for Document Clustering,”2010 IEEE International Conference on Data Mining Workshops, Dec. 14-17, 1196-1203, 2010. (ISTP).
102. Yu, J., B, Xu and Y. Shi, “The domain knowledge driven intelligent data auditing model,”2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Aug. 31-Sept. 3, 199-202, 2010. (ISTP).
101. Niu, L. and Y. Shi, Using Projection Gradient Method to Train Linear Support Vector Machines, 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Aug. 31-Sept. 3, 207-210, 2010. (ISTP).
100. Wang,G., L. Liu, Y. Peng, G. Kou, G. Nie and Y. Shi, “Predicting credit card holder churn in banks of China using data mining and MCDM,”2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Aug. 31-Sept. 3, 215-218, 2010. (ISTP).
99. Wang, X., Y. Zhang, L. Zhang and Y. Shi, “A Knowledge Discovery Case Study of Software Quality Prediction: ISBSG Database,”2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, Aug. 31-Sept. 3, 219-222, 2010. (ISTP).
98. Yu, J., B, Xu and Y. Shi, “The strategic asset allocation optimization model of sovereign wealth funds based on maximum CRRA utility & minimum VAR,” International Conference on Computational Science, ICCS 2010, May 31 - June 2, 2433–2440, 2010.
97. Zhang, Y., P. Zhang, L. Zhang and Y. Shi, “Knowledge Extraction from Multiple Criteria Linear Programming Classification Approach”, International Conference on Computational Science, ICCS 2010, May 31 - June 2, 2441–2448, 2010. (EI, ISTP).
96. Zhou, X., W. Jiang and Y. Shi, “Credit risk evaluation by using nearest subspace method,”International Conference on Computational Science, ICCS 2010, May 31 - June 2, 2449–2455, 2010. (EI, ISTP).
95. Niu, L. and Y. Shi, “A new training method for sequence data,”International Conference on Computational Science, ICCS 2010, May 31 - June 2, 2391–2396, 2010. (EI, ISTP).
94. Zhang, L., M. Peng and Y. Shi, “Study on Knowledge Sharing and Transferring in Quality Management Based on SECI Model,” IMOT2010.
93. Wang, X., L. Zhang,Y. Zhang,Y. Liu and Y. Shi, “Knowledge Discovery Case Study of Software Quality Prediction Based on Classification Models,” ISBSG Database, KSS2010.
92. Zhang, P., L. Zhang, G. Nie, Y. Zhang and Y. Shi, “Transfer Knowledge via Relational K-Means Method,” BIFE 2009, IEEE Computer Society: 656-657, 2009. (ISTP).
91. Yu, J., B. Xu and Y. Shi, “The Pareto-frontier Solution to the Multiproject and Multiple Item Stochastic Chance-Constrained Investment Combination,” BIFE 2009, IEEE Computer Society: 510-513, 2009. (ISTP).
90. Zhang, Y., L. Zhang, G. Nie and Y. Shi, “A Survey of Interestingness Measures for Association Rules,” BIFE 2009, IEEE Computer Society: 460-463, 2009. (ISTP).
89. Zhang, L., J. Li, A. Li, P. Zhang, G. Nie and Y. Shi, “A New research Field: Intelligent Knowledge Management,” BIFE 2009, IEEE Computer Society: 450-454, 2009. (ISTP).
88. Zhou, X., Y. Shi, P. Zhang, G. Nie and W., Jiang, “A New Classification Method for PCA-based Face Recognition,” BIFE 2009, IEEE Computer Society: 445-449, 2009. (ISTP).
87. Zhang, P., Y. Tian, D. Zhang, X. Zhu and Y. Shi, “A Multiple Criteria and Multiple Constraints Mathematical Programming Model for Classification,” MCDM 2009, CCIS 35: 600-605, 2009.
86. Liu, J., J. Li, W. Xu and Y. Shi, “A Two-Layer Least Squares Support Vector Machine Approach to Credit Risk Assessment,” MCDM 2009, CCIS 35: 566-572, 2009. (ISTP).
85. Zhang, D., Y. Tian and Y. Shi, “Nonlinear Knowledge in Kernel-Based Multiple Criteria Programming Classifier” MCDM 2009, CCIS 35: 622-629, 2009. (ISTP).
84. Wang, Y., L. Zhang, X. Zheng and Y. Shi, “Research on Ratchet Effects in Enterprises’ Knowledge Sharing Based on Game Models,” MCDM 2009, CCIS 35: 194-197, 2009. (ISTP).
83. Ma, T., C. Chi, J. Chen and Y. Shi, “A Simulation Model of Technological Adoption with An Intelligent Agent,” MCDM 2009, CCIS 35: 188-193, 2009. (ISTP).
82. Wang, G., F. Li, P. Zhang, Y. Tian and Y. Shi, “Data Mining for Customer Segmentation in Personal Financial Market,” MCDM 2009, CCIS 35: 614-621, 2009. (ISTP).
81. Shi, Y., R. Chen, J. Wan and X. Yang, “A Novel MCQP Approach for Predicting the Distance Range between Interface Residues in Antibody-Antigen Complex,” MCDM 2009, CCIS 35: 643-648, 2009. (ISTP).
80. Huang, A., L. Zhang, Z. Zhu and Y. Shi, “Data Mining Integrated with Domain Knowledge,” MCDM 2009, CCIS 35: 184-187, 2009. (ISTP).
79. Zhang, P., X. Zhu, A. Li, L. Zhang and Y. Shi, “Mining Knowledge from Multiple Criteria Linear Programming Models,” MCDM 2009, CCIS 35: 170-175, 2009. (ISTP).
78. Nie, G., X. Li, L. Zhang, Y. Zhang and Y. Shi, “Knowledge Intelligence: A New Field in Business Intelligence,” MCDM 2009, CCIS 35: 166–169, 2009. (ISTP).
77. Zhang P., X. Zhu, Y. Shi and X. Wu, “An Aggregate Ensemble for Mining Concept Drifting Data Streams with Noise,” PAKDD 2009, LNAI 5476: 1021–1029, 2009. (EI, ISTP).
76. Wang, Y., P. Zhang, G. Nie and Y. Shi, “Multiple Criteria Quadratic Programming for Financial Distress Prediction of the Listed Manufacturing Companies,” ICCS 2009, Part II, LNCS 5545: 616-624, 2009. (EI, ISTP).
75. Zhang,Y., P. Zhang, and Y. Shi, “Kernel Based Regularized Multiple Criteria Linear Programming Model,” ICCS 2009, Part II, LNCS 5545: 625-632, 2009. (EI, ISTP).
74. Zhang, L., Q. Wang, J. Wei, X. Wang and Y. Shi, “The Measurement of Distinguishing Ability of Classification in Data Mining Model and Its Statistical Significance,” ICCS 2009, Part II, LNCS 5545: 578-587, 2009. (EI, ISTP).
73. Zhou, X. and Y. Shi, “Nearest Neighbor Convex Hull Classification Method for Face Recognition,” ICCS 2009, Part II, LNCS 5545: 570-577, 2009. (EI, ISTP).
72. Peng, Y., G. Kou, and Y. Shi, “Knowledge-Rich Data Mining in Financial Risk Detection,” ICCS 2009, Part II, LNCS 5545: 534-542, 2009. (EI, ISTP).
71. Zhang P., X. Zhu and Y. Shi, “Bias-Variance Analysis for Ensembling Regularized Multiple Criteria Linear Programming Models,” ICCS 2009, Part II, LNCS 5545: 524-533, 2009. (EI, ISTP).
70. Nie, G., G. Wang, P. Zhang, Y. Tian and Y. Shi, “Finding the Hidden Pattern of Credit Card Holder’s Churn: A Case of China,” ICCS 2009, Part II, LNCS 5545: 561–569, 2009. (EI, ISTP).
69. Peng, Y., G. Kou, Y. Shi and Z. Chen, “Privacy-Preserving Data Mining for Medical Data: Application of Data Partition Methods,” Studies in Computational Intelligence (SCI) 123: 331–340, 2008.
68. Li, X., J. Li, Y. Zhang and Y. Shi, “A Framework of Knowledge Management Platform for Middle and Small Business,” Studies in Computational Intelligence (SCI) 123: 233-248, 2008.
67. Zhang, Z., Y. Shi, G. Gao, and Y. Chai, “An Effective Feature Selection Method Using the
Contribution Likelihood Ratio of Attributes for Classification,” Ishikawa et al. (Eds.): APWeb 2008 Workshops, LNCS 4977, pp. 165 –171, 2008.
66. Shi, Y., R. Liu, N. Yan, and Z. Chen, “A Family of Optimization Based Data Mining Methods,” Zhang, Y (eds.), ApWeb 2008, Progress in WWW Research and Development, LNCS 4976, pp. 26-38, 2008.
65. Shi, Y., R. Liu, N. Yan, and Z. Chen, “Multiple Criteria Mathematical Programming and Data Mining,” ICCS 2008, Part I: 7-17. (EI, ISTP).
64. Liu, R., N. Yan, Y. Shi, and Z. Chen, “Bound for the L2 Norm of Random Matrix and Succinct MatrixApproximation,” ICCS 2008, Part II: 426-435. (EI, ISTP).
63. Zhang, P., Y. Tian, X. Li, Z. Zhang, and Y. Shi, “Select Representative Samples for Regularized Multiple-Criteria LinearProgrammingClassification,” ICCS 2008, Part II: 436-440. (EI, ISTP).
62. Yan, N., Z. Chen, R. Liu, and Y. Shi, “An Optimization-Based Classification Approach with the Non-additiveMeasure,” ICCS 2008, Part II: 450-458. (EI, ISTP).
61. Zhang, Y., Z. Zhou, and Y. Shi, “A Selection Method of ETF’s Credit Risk Evaluation Indicators”,ICCS 2008, Part II: 459-465. (EI, ISTP).
60. Zhang, Z., Y. Shi, P. Zhang, and G. Gao, “A Rough Set-Based Multiple Criteria Linear Programming Approachfor Classification,” ICCS 2008, Part II: 476-485. (EI, ISTP).
59. Zhang, J. and Y. Shi “A Framework of Optimization Method forClassification,” Lecture Notes in OR: The First International Symposium on Optimization and Systems Biology (OSB’07), Beijing, China, August 8–10, 2007, 391–396. (ISPT).
58. Liu, R. and Y. Shi “Succinct Matrix Approximation and Efficient k-NN Classification,” IEEE ICDM 2007 Proceedings, 213-222. (EI).
57. Zhu, X., P. Zhang, X. Lin and Y. Shi “Active Learning from Data Streams,” IEEE ICDM 2007 Proceedings, 757-762. (EI).
56. He, J., G. Huang, Y. Zhang and Y. Shi “Cluster Analysis and Optimization in Color-Based Clustering for Image,” Workshop on Knowledge Discovery and Data Mining from Multimedia Data and Multimedia Applications, Workshop at IEEE ICDM 2007, 213-218. (EI).
55. Shi, Y., Y. Tian, X. Chen and P. Zhang “A Regularized Multiple Criteria Linear Program for Classification,” Workshop at IEEE ICDM 2007, 253-258. (EI).
54. Zhou, L., Y. Liu, J. Wang and Y. Shi “Utility-based Web Path Traversal Pattern Mining,” Workshop at IEEE ICDM 2007, 373-378. (EI).
53. He, J., Y. Zhang, Y Shi, G. Huang “A Multi-criteria Decision Support System of Water Resource Allocation Scenarios, KSEM2007. (Accepted) (LNAI) (EI, ISTP, DBLP).
52. He, J., Y. Zhang, G. Huang, Y. Shi, “Network Lifetime of Application-Specific Randomly Deployed Wireless Sensor Networks in Arbitrary Sensor Density,” ACIS-ICIS 2007: 352-357. (EI, ISTP, DBLP).
51. Shi, Y. and X. Li "Knowledge Management Platforms and Intelligence Knowledge beyond Data Mining," in Y. Shi, D. Olson and A. Stam, eds., Advance inMultiple Criteria Decision Making and Human Systems Management, IOS Press, Amsterdam, 272-288, 2007.
50.Peng, Z., Zhang, J., and Y. Shi, “A New Multi-Criteria Quadratic-Programming Linear Classification Model for VIP E-Mail Analysis”, ICCS 2007, Part II: 499-502. (EI, ISTP).
49.Meihong,Z., Y. Shi, A. Li and J.He, “A Dynamic Committee Scheme on Multiple-Criteria Linear Programming Classification Method”,ICCS 2007, Part II: 401-480. (EI, ISTP).
48.Yaohui, C., A. Li, Y. Shi, “Kimberlites Identification by Classification Methods”, ICCS 2007, Part II: 409-414. (EI, ISTP).
47.Zhiwang, Z.,Y. Shi, “The Characteristic Analysis of Web User Clusters based on Frequent Browsing Patterns”, ICCS 2007, Part II: 490-493. (EI, ISTP).
46.Jing W., Y. Liu, L. Zhou, Y. Shi, “Pushing Frequency Constraint to Utility Mining Model”. ICCS 2007, Part III: 689-692. (EI, ISTP).
45.Zhan, Z., Y. Tian and Y. Shi, “Feature Selection for VIP E-Mail Accounts Analysis”,ICCS 2007, Part III: 493-700. (EI, ISTP).
44.Peng,Y., G. Kou, J. Matza, Z. Chen, D. Khazanchi and Yong Shi, “Application of Classification Methods to Individual Disability Income Insurance Fraud Detection”,ICCS 2007, Part III: 852-858. (EI, ISTP).
43.Gang, K., Y. Peng, Y. Shi, and Z. Chen, “Epsilon-Support Vector and Large-Scale Data Mining Problems”, ICCS 2007, Part III: 874-881. (EI, ISTP).
42. Li., X, L. Zhang, M. Ding, Y. Shi,J. Li, “A Combined Web Mining Model and Its Application in Crisis Management”, ICCS 2007, Part III: 906-910. (EI, ISTP).
41.Li., G., Z.Zhou, X. Song, and Y. Shi, “A Fuzzy Comprehensive Evaluation Method on Firms' Credit Sale Risk”, ICCS 2007, Part III:1062-1068. (EI, ISTP).
40. Li, X, Y. Shi, Y. Liu, J. Li, and A. Li, “A Knowledge Management Platform for Optimization-based Data Mining”, 6th IEEE International Conference on Data Mining-workshops, 2006. (EI, ISTP).
39. Li, X, Y. Liu, J. Li, Y. Shi, and Y. Zhang, “A Knowledge Management Model for Middle and Small Enterprises,” DCABES 2006 Proceedings, 2006. (ISTP).
38. Shi, Y., Peng, Y., Kou, G., and Chen, Z, “Introduction to Data Mining Techniques via Multiple Criteria Optimization Approaches and Applications” Invited chapter to Advanced Topics in Data Warehousing and Mining, IGI Publisher 2006.
37. Mou, T., Z. Zhou and Y. Shi, “Credit Risk Evaluation based on LINMAP,” ICCS 2006: 452-459. (SCI, EI, ISTP).
36.Kou, G., Y. Peng, Y. Shi and Z. Chen, “A New Multi-Criteria Convex Quadratic Programming Model for Credit Analysis,” ICCS 2006: 476-484. (SCI, EI, ISTP).
35.Kou, G., Y. Peng, Y. Shi and Z. Chen, “Multiclass Credit Cardholders’ Behaviors Classification Methods,” ICCS 2006: 485-492. (SCI, EI, ISTP).
34.He, J., W. Yue and Y. Shi, “Pattern Reorganization for MCNs using Fuzzy Linear Programming,” ICCS 2006: 509-516. (SCI, EI, ISTP).
33. Zhang, L., J. Li, Y. Shi “Study on Improving Efficiency of Knowledge Sharing in Knowledge-Intensive Organization,” WINE 2005: 816-825. (SCI, EI, ISTP, INSPEC).
32. Li, A. and Y. Shi “An Integrated Classification Method: Combination of LP and LDA,” WINE 2005: 758-767. (SCI, EI, ISTP, INSPEC).
31.Kou, G., N. Yan, Y. Peng, N. Yan, Y. Shi and Z. Chen "Network Surveillance and Multi-Group Intrusion Classification," in J. Chen, ed., IEEE Service Systems and Service Management, International Academic Publishers, Beijing, 844-848. (ISTP, INSPEC).
30. Li, J., W. Xu and Y. Shi "Credit Scoring via PCALWM" in V. S. Sunderam et al, eds., ICCS 2005, LNCS 3516, Springer, Berlin, 531-538. (SCI, EI, ISTP, INSPEC).
29. Peng, Y., G. Kou, Y. Shi, and Z. Chen "Improving Clustering Analysis for Credit Card Accounts Classification" in V. S. Sunderam et al, eds., ICCS 2005, LNCS 3516, Springer, Berlin, 548-553. (SCI, EI, ISTP, INSPEC).
28. Dubey, P., Z. Chen and Y. Shi "Using Branch-Grafted R-trees for Spatial Data Mining," in P. M. A. Sloot et al, eds., ICCS 2004, LNCS 2658, Springer, Berlin, 657-660. (SCI, ISTP, INSPEC).
27. Li, J., J. Liu, W. Xu and Y. Shi "Support Vector Machines Approach to Credit Assessment," in P. M. A. Sloot et al, eds., ICCS 2004, LNCS 2658, Springer, Berlin, 892-899. (SCI, ISTP, INSPEC).
26. Peng, Y., G. Kou, Z. Chen, and Y. Shi "Cross-Validation and Ensemble Analyses on Multiple Criteria Linear Programming Classification for Credit Cardholder Behavior," in P. M. A. Sloot et al, eds., ICCS 2004, LNCS 2658, Springer, Berlin, 931-939. (SCI, ISTP, INSPEC).
25.Kou, G., Y. Peng, N. Yan, Y. Shi, Z. Chen, Q. Zhu, J. Huff and S. McCartney "Network Intrusion Detection by using Multiple Criteria Linear Programming," in J. Chen, ed., Service Systems and Service Management, International Academic Publishers, Beijing, 806-809, 2004.
24.Zhou, Z., X. Tang and Y. Shi "A Multi-Factors Evaluation Method on Credit Evaluationof Commerce Banks," in Y. Shi et al, eds., CAS Symposium on Data Mining & Knowledge Management, LNCS 3327, Springer, Berlin, 2004. (SCI, EI, ISTP, INSPEC).
23.Kwak, W., Y. Shi, J. Chehand H. Lee "Multiple Criteria Linear Programming Data Mining Approach: An Application for Bankruptcy Prediction," in Y. Shi et al, eds., CAS Symposium on Data Mining & Knowledge Management, LNCS 3327, Springer, Berlin, 2004. (SCI, EI, ISTP, INSPEC).
22.He, J., Y. Shi and W. Xu "Classifications of Credit Cardholder Behavior by Using Multiple Criteria Non-Linear Programming," in Y. Shi et al, eds., CAS Symposium on Data Mining & Knowledge Management, LNCS 3327, Springer, Berlin, 2004.(SCI, EI, ISTP, INSPEC).
21. Kou, G., Y. Peng, Y. Shi, Z. Chen and X. Chen "A Multiple-Criteria Quadratic Programming Approach to Network Intrusion Detection," in Y. Shi et al, eds., CAS Symposium on Data Mining & Knowledge Management, LNCS 3327, Springer, Berlin, 2004. (SCI, EI, ISTP, INSPEC).
20. Liu, J., J. Li, W. Xu and Y. Shi"Data Mining Approach in Scientific Organization Evaluation via Clustering," in Y. Shi et al, eds., CAS Symposium on Data Mining & Knowledge Management, LNCS 3327, Springer, Berlin, 2004. (SCI, EI, ISTP, INSPEC).
19. Wang, Z., H. Guo, Y. Shi, and K. Leung " A Hybrid Nonlinear Classifiers Based on Generalized Choquet Integrals," in Y. Shi et al, eds., CAS Symposium on Data Mining & Knowledge Management, LNCS 3327, Springer, Berlin, 2004. (SCI, EI, ISTP, INSPEC).
18. Kou, G, Y. Peng, Y. Shi, and W. Xu "A Set of Data Mining Models to Classify Credit Cardholder Behavior," in P. M. A. Sloot et al, eds., ICCS 2003, LNCS 2658, Springer, Berlin, 54-63. (SCI, ISTP, MathSci).
17. Kwak, W., Y. Shi, H. Lee, and C. F. Lee "A Fuzzy Set Approach in International Transfer Pricing Problems," in C. F. Lee, ed., Advance inQuantitative Analysis of Finance and Accounting, Elsevier Science, Amsterdam, 57-74, 2002.
16. Shi, Y., M. Wise, M. Luo and Y. Lin "Data Mining in Credit Card Portfolio Management:
AMultiple Criteria Decision Making Approach," in M. Koksalan and S. Zionts, eds.,
Advance inMultiple Criteria Decision Making in the New Millennium, Springer,
Berlin, 427-436, 2001. (SCI, ISTP).
15. Lee, H., J. Lee, S. Nazem, Y. Shi and J. Stolen, “Performance Management for Corporate
Network, "in James G. Williams ed., Encyclopedia of Microcomputer, Marcel Dekker,
Inc., 323-338, 2001.
14. Shi, Y. and S. Lin "Optimal Trade-off Analysis of Agricultural Policy: A Multiple
Criteria and Multiple Economic Situation Model," in K. Lawrence, G. Reeves and R.
Klimberg eds., Multi-Criteria Applications, Elsevier Science Inc., 165-183, 2000.
13. Shi, Y. and Xiaowo Tang, "The State-of-the-art of MC2 Linear Programming,” in Y. Shi and M. Zeleny eds., New Frontiers of Decision Making for the Information Technology Era, World Scientific Publishing, 304-330, 2000.
12. Lee, H., J. Lee, M. H. Sohn and Y. Shi, "From Enterprise Network to Network Enterprise: Another Perspective of Multiple Criteria Decision Making for building Corporate Information System,” in Y. Shi and M. Zeleny eds., New Frontiers of Decision Making for the Information Technology Era, World Scientific Publishing, 389-402, 2000.
11. Shi, Y. “Data Mining”, in M. Zeleny ed., IEBM Handbook of Information Technology in
Business, International Thomson Publishing Europe, 490-495, 2000.
10. Shi, Y., J. Gu and X. Tang “Information Overload”, in M. Zeleny ed., IEBM Handbook of
Information Technology in Business, International Thomson Publishing Europe,
554-560, 2000.
9. Nazem, S., Y. Shi and H. Lee “Telecommunications and Evolving Techniques”,
in M. Zeleny ed., IEBM Handbook of Information Technology in Business,
International Thomson Publishing Europe, 258-264, 2000.
8. Shi, Y., “Reducing User Information Overload by Humancasting,” in J. Gu, G Fan,
S. Wang and B. Wei, eds, Advances in Operations Research and System
Engineering, Global-Link Informatics, 96-103, 1998.
7. Shi, Y. and Y. H. Liu "A Fuzzy Potential Solution Approach to Multi-Criteria and
Multi-Constraint Level Linear Programming Problems," in J. Climaco, ed,
Multicriteria Analysis, Springer, Berlin, 213-224, 1997. (MathSci).
6. Shi, Y., S. M. Nazem and H. Lee, "Telecommunications," in M. Warner, ed.,
International Encyclopedia of Business and Management, Routledge, United
Kingdom, 4824-4834, 1996.
5. Shi, Y. and P. L. Yu, "Foundations of Designing Optimal Systems and Contingency
Plans," in Ravi P. Agarwal, ed, Recent Trends in Optimization Theory and
Applications, World Scientific Publishing Company, Singapore, 371-391, 1995.
(MathSci).
4. Shi, Y. and P. L. Yu, "An Introduction to Selecting Optimal Linear Systems and
Their Contingency Plans," in G. Fandel and H. Gehring, eds., Operations
Research, Springer, Berlin, 58-77, 1991.
3. Shi, Y. and P. L. Yu, "Habitual Domain Analysis for Effective Decision Making," in:
B. Karpak and S. Zionts, eds., Multiple Criteria Decision Making and Risk
Analysis Using Microcomputers, Springer, Berlin, 127-163,1989.(MathSci).
2. Shi, Y. and P. L. Yu, "Goal Setting and Compromise Solutions," in: B. Karpak and S.
Zionts, eds., Multiple Criteria Decision Making and Risk Analysis Using
Microcomputers, Springer, Berlin, 165-203, 1989.
1. Shi, Y., "Capital Budgeting under Uncertainty: Fuzzy Sets Method, " Collections of
1984 Cross Meeting of Economics and Managerial Petroleum Engineering,
Chengdu, Sichuan, China, July 12-18, Vol. 1, 21-35, 1984. (in Chinese).
Papers in Proceedings:
(EI: 19, ISTP: 4, INSPEC: 6, MathSci: 1 )
73 N. Tasnim, Y. Shi, K. Suo, X. Zhang, “Enhancing Genomic Datasets with cGANs: A Study on Synthetic DNA Sequences for Non-Human Species,” 2024 International Conference on Electrical, Computer and Energy Engineering.
72 C. Gao, Y. Shi, “Prediction Performance Analysis for ML Models Based on Impacts of Data Imbalance and Bias,” Proceedings of the 2024 ACM Southeast Conference, 235-240, 2024.
71. L. Vu, K. Suo, M. R. Islam, N. Dhar, T. N. Nguyen, S. He, Y. Shi, “Living on the Electric Vehicle and Cloud Era: A Study of Cyber Vulnerabilities, Potential Impacts, and Possible Strategies,” Proceedings of the 2024 ACM Southeast Conference, 18-26, 2024.
70. D. C. T. Lo, B. Deng, Y. Shi, “Deep Machine Learning on Segmenting and Classifying Crop Images Taken by Unmanned Aerial Vehicle,” 2023 IEEE International Conference on Big Data (BigData), 3470-3478, 2023.
69. J. Priest, C. Cooper, S. Lovell, Y. Shi, D. Lo, “Design and Implementation of an ERC-20 Smart Contract on the Ethereum Blockchain,” 2023 IEEE International Conference on Big Data (BigData), 2334-2338, 2023.
68. Y. Shi, N. Sakib, H. Shahriar, D. Lo, H. Chi, K. Qian, “AI-Assisted Security: A Step towards Reimagining Software Development for a Safer Future,” 2023 IEEE 47th Annual Computers, Software, and Applications Conference (COMPSAC), 2023.
67. D. Bandi, Y. Shi, H. Shahriar, D. Lo, K. Suo, H. Chi, K. Qian, “Quantum Machine Learning for Security Data Analysis,” 2023 IEEE World AI IoT Congress (AIIoT), 0460-0465, 2023.
66. T. Potluri, Y. Shi, H. Shahriar, D. Lo, R. Parizi, H. Chi, K. Qian, “Secure Software Development in Google Colab,” 2023 IEEE World AI IoT Congress (AIIoT), 0398-0402, 2023.
65. W. Downing, D. Harvey, D. Wagura, Y. Shi, “Blockchain Development in Colab: An Ethereum-Based Bicycle Registry System,” 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), 2023.
64. H. Lupsan, R. Ahmed, Y. Shi, “Cybersecurity in Malware Research,” 2023 IEEE 13th Annual Computing and Communication Workshop and Conference (CCWC), 2023.
63. Yang Jie, Qi Zhiquan, Shi Y., Learn to Incorporate Structure Knowledge for Image Inpainting, the Association for the Advance of Artificial Intelligence (AAAI), 2019.
62. Liu Jiabin, Wang Bo, Qi Zjiquan, Tian Yingjie, Shi Y., Learning from Label Proportions with Generative Adversarial Networks, Conference and Workshop on Neural Information Processing Systems(NIPS), 2019.
61. Shi, Y., Zheng, Y., Guo, K., Zhu, L., Qu, Y., Intrinsic and Extrinsic Evaluation: An Overview of Word Embedding Evaluation. In: 2018 IEEE International Conference on Data Mining Workshops (ICDMW), 1255-1260, 2018.
60. Z. Qi, Y. Tian, and Y. Shi, "Regularized multiple criteria second order cone programming formulations," Proceedings of KDD, DMIKM, 2012(EI).
59. Z. Qi, Y. Tian, and Y. Shi, "Regular Multiple Criteria Linear Programming for Semi-supervised Classification," Proceedings of ICDM, 2012(EI).
58. Z. Zhang, D. Zhang, Y. Tian and Y. Shi “Kernel Based Multiple Criteria Linear Program,” The 19th International Conference on Multiple Criteria Decision Making (MCDM), Auckland, New Zealand, Jan. 7-12, 2008, 55-57.
57. J. He, Y. Shi, Y. Zhang and A. Li “Multiple Criteria and Multiple Constraint Level Linear Programming for Discriminant Problems,” The 19th International Conference on Multiple Criteria Decision Making (MCDM), Auckland, New Zealand, Jan. 7-12, 2008, 53-54.
56. N.Yan, Y. Shi and Z. Chen “Multiple Criteria Nonlinear Programming Classification with Signed Non-additive Measure”, The 19th International Conference on Multiple Criteria Decision Making (MCDM), Auckland, New Zealand, Jan. 7-12, 2008, 97-98.
55. Fu, H.,L. Zhang,Y. Shi, “The Application of Data Mining in Mobile Subscriber Classification”, The 3rd International Conference on Natural Computation (ICNC'07) and the 4th International Conference on Fuzzy Systems and Knowledge Discovery (FSKD'07) will be jointly held in Haikou, China. Haikou.
54. HE, J., Y. Zhang, G. Huang, Y. Shi, “Network Lifetime of Application-Specific Randomly Deployed Wireless Sensor Networks in Arbitrary Sensor Density”, 6th IEEE International Conference on Computer and Information Science, Melbourne, 2007.
53. Zhang, Y., L. Zhang, Y. Shi, “Research on Business Process-oriented Knowledge Auditing Model”, International Conference on Management, ICM2007, Wuhan.
52. Pi, J., Y. Shi and Z. Chen, “From similarity retrieval to cluster analysis: The case of R*-trees”, Proc. IEEE Symposium on Computational Intelligence and Data Mining (CIDM 2007) .
51. Liu, R., Y. Shi, “A RBF Classifier with Supervised Center Selection and Weighted Norm”,Proceeding of workshops on The Sixth IEEE International Conference on Data Mining(ICDM), HongKong, Dec 19-22, 2006. (EI).
50. Kou, G., Y. Peng, Y. Shi and Z. Chen, "Network Intrusion Detection by Multi-groupMathematical Programming based Classifier", Proceeding of workshops on The Sixth IEEE International Conference on Data Mining(ICDM), HongKong, Dec 19-22, 2006. (EI).
49. Peng, Y., G. Kou, Y.Shi and Z. Chen, "A Systemic Framework for the Field of Data Miningand Knowledge Discovery", Proceeding of workshops on The Sixth IEEE International Conference on Data Mining (ICDM), HongKong, Dec 19-22, 2006. (EI).
48. Aihua, L., Y. Shi, etc. “A Data Mining Approach to Classify Credit Cardholders’Behavior”,Proceeding of workshops on The Sixth IEEE International Conference on Data Mining(ICDM), HongKong, Dec 19-22, 2006. (EI).
47. Peng, Y., G. Kou, Y. Shi and Z. Chen, "A Hybrid Strategy for Clustering Data MiningDocuments", Proceeding of workshops on The Sixth IEEE International Conference on Data Mining(ICDM), HongKong, Dec 19-22, 2006. (EI).
46. Li, X., Y. Shi, Y. Liu, J. Li, and A. Li, "A Knowledge Management Platformfor Optimization-based Data Mining", Proceeding of workshops on The Sixth IEEE International Conference on Data Mining(ICDM), HongKong, Dec 19-22, 2006. (EI).
45.Nie, G., L. Zhang, X. Li and Y. Shi , “The Analysis on the CustomersChurn of Charge Email Based on Data Mining -Take One Internet Company for Example”, Proceeding of workshops on The Sixth IEEE International Conference on Data Mining(ICDM), HongKong, Dec 19-22, 2006. (EI).
44.Li, X., Y. Liu, J. Li, Y. Shi, Y. Zhang, “A KNOWLEDGE MANAGEMENTMODEL FOR MIDDLE AND SMALL ENTERPRISES”, proceedings of 2006 International Symposiumon Distributed Computing and Applications for Business, Engineering, and Sciences, Hangzhou, China,Oct., 2006, 924－930.
43. Kou, G., Y. Peng, Y. Shiand Z. Chen, "Privacy-preserving Data Mining of Medical Datausing Data Separation Based Techniques" the 20th CODATA 2006 Discovery Workshop onInterdisciplinary Communication for Risk Management with Multi-Data Mining, Beijing, China, Oct. 23 - 27, 2006.
42. Li, X., J. Li, Y. Zhang, Y. Shi, “A Framework of Knowledge ManagementPlatform for Middle and Small Business”. The 20th CODATA International Conference, Scientific Dataand Knowledge within the Information Society, Beijing, China, October .23-25, 2006.
41.Peng, Y., G. Kou, A. Sabatka, Z. Chen, D. Khazanchi, Y. Shi, “Application of ClusteringMethods to Health Insurance Fraud Detection”,The 3rd IEEE/SSSM 2006 International Conference onService Systems and Service Management, The University of Technology of Troyes,France, Oct 25 - 27, 2006.
40. Peng, Y., G. Kou, Y. Shi and Z. Chen,“Recent trends in Data Mining (DM): DocumentClustering of DM Publications”, The 3rd IEEE/SSSM 2006 International Conference on Service Systemand Service Management, The University of Technology of Troyes, France, Oct 25 - 27, 2006.
39. Kou, G., Y. Peng, Y. Shi and Z. Chen, “Apply Mathematical Programming in Banking andFinancial Industry”, Proceedings of Modern Industry Economy & Management,Maansan, China , April 21-23, 2006, 396-401.
38. Peng, Y., G. Kou, Y. Shi and Z. Chen,“What is current Data Miner doing? – Documentclustering on Data Mining publications”Proceedings of Modern Industry Economy & Management,Maansan, China, April 21-23, 2006, 81-85.
37. Pi, J., Y. Shi, Z. Chen, “Fast Similarity Analysis for Time Series Data Using PCA with R*-Trees”, Proc. VII International Workshop Computational Problems of Electrical Eng., 2006, 1-4.
36. Pi, J., Y. Shi, Z. Chen, “Evaluation of Cluster Analysis Algorithms Enhanced by Using R*-Trees”, Proc. ACS/IEEE Computer Systems and Application, .2006, 600 -607.
35.Yan, N., Z. Wang, Y. Shi, Z. Chen, “Nonlinear Classification by Linear Programming with Signed Fuzzy”, 2006 IEEE International Conference on Fuzzy Systems, Vancouver, Canada, July 16-21, 2006.
34.Peng, Y., N. Yan, G. Kou, Z. Chen, Y. Shi, “Document Clustering in Antimicrobial Peptides Research”, Proceedings of the Eleventh Americas Conference on Information Systems, August 11-14, 2005.
33.Wei, Y., Q. Yang, S. Yao and Y. Shi, “Hierarchical Clustering Analysis from Genomic Dataset," 2005 IEEE/WIC/ACM International Conference on Intelligent Agent Technology, France, 2005, 759-762. (ISTP, INSPEC).
32. Pi, J., Y. Shi and Z. Chen, “Similarity and Cluster Analysis Algorithms for Microarrays Using R*-Trees,” IEEE CSB 2005 Workshops and Poster Abstracts, Stanford University, California, Aug. 8-11, 2005, 91-92. (INSPEC).
31. Peng, Y., G. Kou, Y. Shi, Z. Chen and H. Yang, “A Comparison Study of Multiclass Classification between Multiple Criteria Mathematical Programming and Hierarchical
Method for Support Vector Machines," 2005 ICDM Workshop: Optimization-based Data Mining Techniques with Applications, U.S.A., 2005, 30-36.
30. He, J., W. Yue and Y. Shi, “Pattern Recognition for Multimedia Communication Networks Using New Connection Models," 2005 ICDM Workshop: Optimization-based Data Mining Techniques with Applications, U.S.A., 2005, 37-42.
29. He, J., W. Yue and Y. Shi, “Identification Mining of Unusual Patterns for Multimedia Communication Networks," Abstract Proc. of Autumn Conference 2005 of Operations Research Society of Japan, 2005, 262-263.
28. He, J., W. Yue and Y. Shi, “A Double Helix Architecture of Knowledge Discovery System Based on Data Grid and Knowledge Grid for Multimedia Communication Networks," Proc. of 1st Intel. Cong. of the Intel. Federation for Systems Research, Japan, 2005, 123-124.
27. He, J., W. Yue and Y. Shi, “Data Mining Systems of QoS Integrated Evaluation for Multimedia Communication Networks," Proc. of IICT Symposium, Konan University, 2005 ,14- 21.
26.Wang, M., J. Zheng, Z. Chen, and Y. Shi, “Classification Methods for HIV-1 Medicated Neuronal Damage,” IEEE CSB 2005 Workshops and Poster Abstracts, Aug. 8-11, 2005, Stanford University, California, 31-32. (INSPEC).
25.Peng, Y, N. Yan, G. Kou, Z. Chen and Y. Shi “Document Clustering in Antimicrobial Peptides Research,” Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA August 11th-14th 2005, 878-887.
24.Peng, Y, G. Kou, Y. Shi and Z. Chen “Using Optimization-Based Classification Method for Massive Datasets,” Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA August 11th-14th 2005, 1446-1452.
23. Zhang, L., Y. Shi and X. Yang “A Fuzzy Mining Algorithm for Association-Rule Knowledge Discovery,” Proceedings of the Eleventh Americas Conference on Information Systems, Omaha, NE, USA, August 11-14, 2005, 1487-1496.
22 Kou, G, Y. Peng, Y,N. Yan, Y. Shi, Z. Chen, Q. Zhu, J. Huff, S. McCartney, “Network intrusion detection by using multiple-criteria linear programming”, Proceedings of ICSSSM '04, Beijing, China , 2004, Vol.1, 806-809. (ISTP).
21. Zheng, J., D. Erichsen, C. Williams, H. Peng, G. Kou, C. Shi and Y. Shi, “Classifications
of Neural Dendritic and Synaptic Damage Resulting from Hiv-1-Associated Dementia:
A Multiple Criteria Linear Programming Approach”, The Proceedings of the 36th Annual Hawaii International Conference on System Sciences, Big Island, Hawaii, Jan. 6-9, 2003. (INSPEC).
20. Kou, G., Y. Peng, Y. Shi, M. Wise and W. Xu, “Four-group Classification Analysis for Credit Cardholder Behavior”, The Proceedings of International Conference on Intelligent Information Technology, Beijing, China, Sept. 22-25, 2002.
19 Tang, X., Z. Zhou, Y. Shi,” The errors bounds of optimal combined forecasting”Proceedings of the 2001 International Conference on Management Science and Engineering, Chengdu, Sichuan, China, 2001, Vol.1, 1507-1512. (ISTP, MathSci).
18. Peng, Y., Y. Shi and W. Xu, “Classification for Three-group of Credit Cardholders’
Behavior Via A Multiple Criteria Approach”, D. Li, ed., The Proceedings of the Fifth International Conference on Optimization: Techniques and Applications, Hong Kong, China, 2001, 1279-1286.
17. Shi, Y., W. Kwak, H. Lee., " Capital budgeting with multiple criteria and multiple decision makers: a fuzzy approach," The Proceedings of the Eighth International Fuzzy Systems Association World Congress, Nebraska Univ., Omaha, NE, USA ,1999,Vol.2, 1004-1008. (INSPEC).
16. Shi, Y., "Development Pattern and Strategy of Creative Intelligence: Information
Technology and Its Commercialization," The Proceedings of the Conference of
Creative Intelligence’s Development Strategy for 21 Century, Beijing, China,
September 22-24, 1999, 28-33.
15. Shi, Y., "Humancasting: A Fundamental Method to Overcome Computer Network
Information Overload," The Proceedings of the Third CAST Conference of
Young Scientists, Beijing, China, August 20-22, 1998, Vol. 1, 3-9.
14. Shi, Y., "MC2 Linear Programming: A Tool for Quantitative Management," The
Proceedings of the First International Conference on Operations and
Quantitative Management, Jaipur, India, Jan. 5-8, 1997, Vol. 1, 91-98. (ISTP).
13. Shi, Y., W. Kwak, H. Lee and C. F. Lee, "Capital Budgeting with Multiple Criteria and
Multiple Decision Makers: A Fuzzy Approach," The Proceedings of the First
International Conference on Operations and Quantitative Management, Jaipur,
India, Jan. 5-8, 1997, Vol. 1, 83-90.
12. Zhou, Z and Y. Shi, "The Applications of ODE Techniques in Multiobjective
Programming," The Proceedings of the First International Conference on
Operations and Quantitative Management, Jaipur, India, Jan. 5-8, 1997, Vol. 1,
99-104. (INSPEC).
11. Shi, Y., W. Kwak and H. Lee, "Optimal Trade-offs of Multiple Factors in International
Transfer Pricing Problems," The Proceedings of Pan-Pacific Conference XIII: A
Business Economic and Technological Exchange, Chida, Japan, May 28-31,
1996, 411-413.
10. Shi, Y., "MC2 Linear Programming: Theory and Applications," G. Liu, K. Phua, J. Ma,
J. Xu, F. Gu, and C. He eds., The Proceedings of the Third International
Conference on Optimization: Techniques and Applications, Chengdu, China,
World Scientific, Singapore, 1995, 584-593.
9. Kwak, W., Y. Shi, H. Lee and C. F. Lee, "Capital Budgeting with Multiple Criteria and
Multiple Decision Makers," G. Liu, K. Phua, J. Ma, J. Xu, F. Gu, and C. He eds., The
Proceedings of the Third International Conference on Optimization: Techniques and
Applications, Chengdu, China, World Scientific, Singapore, 1995, 541-550.
8. Liu, Y., Y. Shi and Y. Liu, "A Fuzzy Duality of MC2 Linear Programming," G. Liu, K.
Phua, J. Ma, J. Xu, F. Gu, and C. He eds., The Proceedings of the Third
International Conference on Optimization: Techniques and Applications,
Chengdu, China, World Scientific, Singapore, 1995, 551-560.
7. Lee, G., Y. Liu and Y. Shi, "Models of Engineering Economic Decision-making for
Chinese Petroleum Industry," G. Liu, K. Phua, J. Ma, J. Xu, F. Gu, and C. He eds.,
The Proceedings of the Third International Conference on Optimization:
Techniques and Applications, Chengdu, China, World Scientific, Singapore, 1995, 1333-1340.
6. Nazem, S., Y. Liu, Y. Shi and H. Lee, "Supporting Rural Telecommunications and
Policy Implications: Multicriteria Perspectives," G. Liu, K. Phua, J. Ma, J. Xu, F.
Gu, and C. He eds., The Proceedings of the Third International Conference on
Optimization: Techniques and Applications, Chengdu, China, World Scientific,
Singapore, 1995, 1632-1641.
5. Shi, Y., "Optimal Linear Designs and Contingency Plans" The Proceedings of the First
Conference on Management Science for Chinese Domestic and Overseas Young
Scientists, Beijing, China, July 19-22, 1994, 230-235.
4. Shi, Y., "Optimal Production System Designs and Contingency Plans: An MC2
Simplex Method Approach," The Proceedings of 1993 Academia Sinica Conference
on Scientific and Engineering Computing for Young Chinese Scientists,
Beijing, China, August 16-21, 1993, 353-358.
3. Shi, Y., "Optimal Production System Designs and Contingency Plans: A Model for
Competitive Global Economy," The Proceedings of Pan-Pacific Conference X: A
Business Economic and Technological Exchange, Beijing, China, June 10-12,
1993, 206-208.
2. Shi, Y., "A Multiple-Criteria Decision Making Approach to Generalized Linear
Production Systems," The Proceedings of DSI International Conference in Seoul,
Korea, June 14-16, 1993, 117-120.
1. Shi, Y. and P. L. Yu, "Generalized Optimal Linear Production Systems in Multiple
Criteria Environments," The Proceedings of The Tenth International Conference
on Multiple Criteria Decision Making, Taipei, Taiwan, R.O.C., July 19-24, 1992,
Vol. 2, 161-170.
Presentations at Conferences
49. Shi, Y., “Data Mining Techniques via Multiple Criteria Optimization Approaches,” A Keynote Lecture, Workshop on Mathematical Programming in Data Mining and Machine Learning, McMaster University, Hamilton, ON Canada, June 1-4, 2005.
48. Shi, Y., “Optimization-based Data Mining in Credit Card Risk Management and Other Applications,” A Keynote Lecture, the 17th RAMP Symposium, Hirosaki, Japan, Oct. 20-22, 2005.
47. Shi, Y., "Strategy of Developing Talents and Non-Profit Consulting Firms in China," the International Forum on the Medium and Long-term Development Planning for China’s Science and Technology, Beijing, Nov. 13-14, 2003.
46. Shi, Y., "Credit Card Business Intelligence by Using Linear Programming-based Data Mining Techniques," A Tutorial Speech at the INFORMS Annual Meeting, Atlanta, GA, Oct. 19-22, 2003.
45. Shi, Y., J. He and X. Liu, "Data Mining on Credit Cardholder Behaviors by Using Fuzzy Linear Programming," Presented at the INFORMS Annual Meeting, Atlanta, GA, Oct. 20-22, 2003.
44. Kou, G, Y. Peng, Y. Shi, and W. Xu "A Set of Data Mining Models to Classify Credit Cardholder Behavior," Presented at the Computational Science-ICCS 2003, St. Petersburg, Russia, June.2-4, 2003.
43. Kou, G., Y. Peng, Y. Shi, M. Wise and W. Xu, “Using Multi-objective Linear Programming to Classify Credit Cardholder Behavior”, The Second Japanese-Sino Optimization Meeting, Kyoto, Sept. 25-27, 2002.
42. Shi, Y., "Linear Programming-based Data Mining techniques and Credit card Knowledge Management," A Keynote Speech at the International Symposium on Knowledge and Systems Sciences, Shanghai, China, August 7-8, 2001.
41. Peng, Y., Y. Shi and W. Xu, “Using Multi-criteria Linear Programming to Classify Credit Cardholders’ Behavior,” Presented at the International Workshop on Decision Making under Uncertainty The Chinese Academy of Sciences, Beijing, China, May.27-28, 2002.
40. Kwak, W., Y. Shi and K. Jung, "Human Resource Allocation in A CPA Firm: A Fuzzy Approach," Presented at the Ninth Annual Conference on Pacific Basin Finance, Economics and Accounting, New Jersey, Sept. 21-22, 2001.
39. Shi, Y., "Linear Approaches to Data Mining," A Keynote Speech at the Seminar of Data Analysis, Financial Physics and Risk Management organized by China High-Tech Center, Chinese Academy of Sciences, Beijing, China, August 13-17, 2001.
38. Shi, Y., "Credit Score Evaluation System in Financial Market," A Keynote Speech at the Seminar of Data Analysis, Financial Physics and Risk Management organized by China High-Tech Center, Chinese Academy of Sciences, Beijing, China, August 13-17, 2001.
37. Shi, Y. and Y. Peng, "Classification for Credit Card Portfolio Management via A Multiple Criteria Approach," Presented at the INFORMS International Conference, Hawaii, June 18-21, 2001.
36. Shi, Y., "Evaluation of Information Security Software," Presented at the CERT Conference 2000, Omaha, Nebraska, September 26-28, 2000.
35. Shi, Y., "Data Mining in Credit Card Portfolio Management: A Multiple-Criteria Decision Making Approach," Presented at The Fifteenth International Conference on Multiple Criteria Decision Making, Ankara, Turkey, July 10-14, 2000.
34. Shi, Y., "State-of-the –Art of MC2 Linear Programming" Presented at the INFORMS- KORMS Conference, Seoul, Korea, June 18-21, 2000.
33. Zhong,Y. and Y.Shi, "An Interior-Point Approach for Solving MC2 Linear Programming," Presented at the INFORMS-KORMS Conference, Seoul, Korea, June 18-21, 2000.
32. Li, J. and Y. Shi, " A Dynamic Transportation Model with Multiple Criteria and Multiple Constraint Levels," Presented at the INFORMS-KORMS Conference, Seoul, Korea, June 18-21, 2000.
31. Li, J. and Y. Shi, "An Integer Linear Programming with Multi-Criteria and Multi-Constraint Levels: A Branch-and-Partition Algorithm," Presented at the INFORMS-KORMS Conference, Seoul, Korea, June 18-21, 2000.
30. Zhong, Y. and Y. Shi, "Duality of Fuzzy MC2 Linear Programming: A Parametric Approach," Presented at the INFORMS-KORMS Conference, Seoul, Korea, June 18-21, 2000.
29. Kwak, W., Y. Shi, H. Lee and C. F. Lee, "A Fuzzy Set Approach in International Transfer Pricing Problems," Presented at the Eighth Pacific Basin Finance, Economics, and Accounting Conference, Bangkok, Thailand, June 1-2, 2000.
28. Shi, Y., "Development Pattern and Strategy of Creative Intelligence: Information Technology and Its Commercialization," A Keynote Speech at the Conference of Creative Intelligence’s Development Strategy for 21 Century, Beijing, China, September 22-24, 1999, 28-33.
27. Shi, Y., W. Kwak, H. Lee and C. F. Lee, "A Fuzzy Solution to Capital Budgeting with Multiple Criteria Multiple Decision Makers," Presented at the Eighth International Fuzzy Systems Association World Congress, Taipei, Taiwan, August 16-20, 1999.
26. Shi, Y., “Traditional Sciences Face Challenges of the High-Tech Development,” A Keynote Speech at the 110th XiangShan Science Conference, Chinese Academy of Sciences, Beijing, December 22-23, 1998.
25. Shi, Y., "Humancasting: A Fundamental Method to Overcome Computer Network Information Overload," A Keynote Speech at the Third CAST Conference of Young Scientists, Beijing, China, August 20-22, 1998.
24. Shi, Y., "Multiple Criteria Decision Making in Information and Telecommunications Systems," Presented at The Fourteenth International Conference on Multiple Criteria Decision Making, Charlottesville, Virginia, June 8-12, 1998.
23. Shi, Y., " MC2 Linear Programming: Theory and Applications," Presented at The Fourteenth International Conference on Multiple Criteria Decision Making, Charlottesville, Virginia, June 8-12, 1998.
22. Shi, Y., "MC2 Linear Programming: A Tool for Quantitative Management," Presented at the First International Conference on Operations and Quantitative Management, Jaipur, India, Jan. 5-8, 1997. (INSPEC)
21. Shi, Y., W. Kwak, H. Lee and C. F. Lee, "Capital Budgeting with Multiple Criteria and Multiple Decision Makers: A Fuzzy Approach," Presented at the First International Conference on Operations and Quantitative Management, Jaipur, India, Jan. 5-8, 1997. (ISTP, INSPEC)
20. Zhou, Z and Y. Shi, "The Applications of ODE Techniques in Multiobjective Programming," Presented at the First International Conference on Operations and Quantitative Management, Jaipur, India, Jan. 5-8, 1997. (ISTP)
19. Shi, Y. and P. L. Yu, "MC2 Linear Programming: Application Respective," Presented at INFORMS Annual Meeting, Washington, D. C., May 5-8, 1996.
18.Shi, Y., "Theory and Applications of MC2 Linear Programming." A Tutorial Speech at The First INFORMS International Meeting, Singapore, June 25-28, 1995.
17. Shi, Y., Z. Huang and H. Li, "A Pareto-Koopmans Efficient Method for Group Decision Making Units in Data Envelopment Analysis," Presented at The First INFORMS International Meeting, Singapore, June 25-28, 1995.
16. Li, G., Y. Liu and Y. Shi, "Quantitative Analysis of Engineering Economic Problems in Chinese Petroleum Industry," Presented at The First INFORMS International Meeting, Singapore, June 25-28, 1995.
15. Shi, Y., "Optimum-Path Ratios in Multicriteria De Novo Programming Problems," Presented at The Eleventh International Conference on Multiple Criteria Decision Making, Coimbra, Portugal, August 1-6, 1994.
14. Shi, Y. and Y. H. Liu, "A Fuzzy Potential Solution Approach to Multi-Criteria and Multi-Constraint Level Linear Programming Problems," Presented at The Eleventh International Conference on Multiple Criteria Decision Making, Coimbra, Portugal, August 1-6, 1994.
13. Shi, Y., "Optimal Linear Production Designs with Multicriteria and Multiresource Levels," Presented at TIMS/ORSA Joint National Meeting, Boston, April, 24-27, 1994.
12. Liu, Y. H. and Y. Shi, "A Fuzzy Programming Approach for Solving A Multiple Criteria and Multiple Constraint Level Programming Problem," Presented at TIMS/ORSA Joint National Meeting, Boston, April, 24-27, 1994.
11. Shi, Y. and H. Lee, "A Multicriteria and Multiconstraint Level Binary Integer Linear Programming," Presented at TIMS/ORSA Joint National Meeting, Chicago, May 16-19, 1993.
10. Shi, Y. and P. L. Yu, "Formulating Aggregate Production Planning by Multi-Criteria and Multi-Constraint Level Simplex Method," Presented at TIMS/ORSA Joint National Meeting, Chicago, May 16-19, 1993.
9. Lee, H., Y. Shi and S. M. Nazem, "Supporting Rural Telecommunication Network via Hub Cities: A Zero-One Compromise Model," Presented at TIMS/ORSA Joint National Meeting, Chicago, May 16-19, 1993.
8. Shi, Y., "Designing Optimal Contingency Plans for Linear Production Systems: Contribution Adjustment Approach," Presented at DSI Annual Meeting, San Francisco, California, Nov. 22-24, 1992.
7. Shi, Y., P. L. Yu, C. Zhang and D. Zhang, "Optimal Generalized Linear Production Systems and Optimal Contingency Plans," Presented at TIMS/ORSA Joint National Meeting, Orlando, Florida, April 26-29, 1992.
6. Shi, Y., P. L. Yu and C. Zhang, "Selecting Optimal Linear Production Systems with Fuzzy Parameters," Presented at TIMS/ORSA Joint National Meeting, Orlando, Florida, April 26-29, 1992.
5. Shi, Y., P. L. Yu, C. Zhang and D. Zhang. "Eliminating Permanently Dominated Opportunities in Linear Production Design," Proceedings of DSI Annual Meeting, Miami Beach, Nov. 24-26, 1991.
4. Shi, Y. and P. L. Yu, "Selecting Optimal Linear Production Systems in Multiple Criteria Environments," Presented at TIMS/ORSA Joint National Meeting, Nashville, Tennessee, May 12-15, 1991.
3. Shi, Y. and P. L. Yu, "Constructing Dual Optimal Contingency Plans for Linear Optimal Designs," Presented at CORS/90, Ottawa, Canada, May 22-24, 1990.
2. Shi, Y. and P. L. Yu, "Structure of Linear Optimal Contingency Plans in Linear Optimal Design Problems," Presented at CORS/TIMS/ORSA Joint National Meeting, Vancouver, Canada, May 8-10, 1989.
1. Lee, Y. R., Y. Shi and P. L. Yu, "Construct Optimal Contingency Plans for Linear Optimal Design Problems," Presented at the Eighth International Conference on Multiple Criteria Decision Making, Manchester, England, August 1988.
COMPUTER SOFTWARE DEVELOPMENT
11. Yan, N. and Y. Shi, “Neural Network Classification Program: version 1.0,” A C++ Program run PC, College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA, 2003.
10. Kou, G. and Y. Shi, “Linux based Multiple Linear Programming Classification Program: version 1.0,” College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA, 2002.
9. Shi, Y., Y. Peng and M. Wise, “SAS based Multiple Linear Programming ClassificationProgram: version 1.0,” College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA, 2002.
8. Wang, L. and Y. Shi, “MC2 Integer Program: version 2.0,” A C++ Program run PC, College of Information Science and Technology, University of Nebraska-Omaha,Omaha, NE 68182, USA, 2002.
7. Fan, W. and Y. Shi, “MC2 Integer Program: version 1.0,” A C++ Program run PC, College of Information Science and Technology, University of Nebraska-Omaha,Omaha, NE 68182, USA, 2000.
6. Ge, Y. S. and Y. Shi, “MC2 Program: A Window NT version on PC,” College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA, 1997.
5. Hao, X. R and Y. Shi, "MC2 Binary Integer Program: version 1.0," A C++ Program run PC or Unix, College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA, 1997.
4. Huang, H. B and Y. Shi, " MC2 Transportation Programs: version 2.0," A C++ Program run PC or Unix, College of Information Science and Technology, University of Nebraska-Omaha, Omaha, NE 68182, USA, 1997.
3. Hao, X. R and Y. Shi, "Large-scale MC2 Program: version 1.0," A C++ Program run on PC or Unix, College of Information Science and Technology, University ofNebraska-Omaha, Omaha, NE 68182, USA, 1996.
2. Haase, C. and Y. Shi, "MC2 Trasp Program: version 1.0," A C++ Program run on PC or Unix, College of Business Administration, University of Nebraska-Omaha, Omaha, 68182, USA, 1994.
1. Chien, I. S., Y. Shi and P. L. Yu, "MC2 Program," A Pascal Program run on PC or VAX, School of Business, University of Kansas, Lawrence, KS 66045, USA, 1989.
