Professor, Information Technology Management
Ph.D., Artificial Intelligence, University of Pittsburgh
M. Tech., Computer Science, University of Calcutta, India
B. Sc., Physics, University of Calcutta, India
Dr. Sinha specializes in the areas of business intelligence, data warehousing, and service-oriented systems. His current research interests are in business analytics, data/text mining, healthcare informatics, and service-oriented computing. He has taught a wide variety of courses at both the graduate and undergraduate levels. He has developed and taught new courses in business intelligence, data warehousing, IT for strategic enterprise management, service-oriented business systems, and object-oriented analysis and design. He has also developed and offered doctoral seminars in data mining, text mining, and design science research. Dr. Sinha recently chaired a task force at the Lubar School for developing an online Graduate Certificate in Business Analytics He is also one of the key faculty members involved in the Graduate Certificate in ERP,where he uses SAP Business Information Warehouse, SAP Crystal Dashboard, and Business Objects.
Dr. Sinha’s research has been published in several journals, including ACM Transactions on MIS, Communications of the ACM, Decision Support Systems, IEEE Transactions on Engineering Management, IEEE Transactions on Software Engineering, IEEE Transactions on Systems, Man, And Cybernetics, Information Systems Research, International Journal of Human-Computer Studies, Journal of AIS, Journal of Biomedical Informatics, and Journal of MIS. Dr. Sinha has been the recipient of several Lubar School of Business awards, including the Roger L. Fitzsimonds Distinguished Scholar Award, the Izzet Sahin Research Award, the Business Advisory Council Research Fellow Award, and the Teaching Excellence Award. He is a member of ACM, AIS, and INFORMS, and served as the chair of the Workshop on Information Technologies and Systems (WITS) in 2006 and the chair of the International Conference on Design Science Research in Information Systems and Technology (DESRIST) in 2011. He also served as the Associate Editor of MIS Quarterly for special issues in Design Science Research and Business Intelligence Research.
Sample of Recent Publications
“Clinical Decision Support: Converging toward an Integrated Architecture,” Journal of Biomedical Informatics, 45(5), 2012, 1009-1017.
“Analyzing Online Review Helpfulness Using a Regressional ReliefF-Enhanced Text Mining Method,” ACM Transactions on Management Information Systems, 3(2), 2012, 10:1-10:20.
“A Model of Data Warehousing Process Maturity,” IEEE Transactions on Software Engineering, 38(2), 2012, 336-353.
Service-Oriented Perspectives in Design Science Research, (Eds.), Lecture Notes in Computer Science 6629, Springer-Verlag, 2011.
“An Extended Tuning Method for Cost-Sensitive Regression and Forecasting” Decision Support Systems, 51(3), 2011, 372-383.
“IT Alignment Strategies for Customer Relationship Management,” Decision Support Systems, 51(3), 2011, 609-619.
“A Hybrid Attribute Selection Approach for Text Classification,” Journal of the Association for Information Systems, 11(9), 2010, 491-518.
“Tuning Data Mining Methods for Cost-Sensitive Regression: A Study in Loan Charge-Off Forecasting,” Journal of Management Information Systems, 25(3), 2009, 315-336.
“Incorporating Domain Knowledge into Data Mining Classifiers: An Application in Indirect Lending,” Decision Support Systems, 46(1), 2008, 287-299.
“Data Warehousing Infusion and Organizational Effectiveness,” IEEE Transactions on Systems, Man, and Cybernetics—Part A, 38(4), 2008, 976-994.
“An Empirical Investigation of the Key Determinants of Data Warehouse Adoption,” Decision Support Systems, 44(4), 2008, 817-841.
“Toward Developing Data Warehousing Process Standards: An Ontology-Based Review of Existing Methodologies,” IEEE Transactions on Systems, Man, and Cybernetics—Part C, 37(1), 2007, 17-31.
“A Comparison of Data Warehousing Methodologies,” Communications of the ACM, 48(3), 2005, 79-84.
“Evaluating and Tuning Predictive Data Mining Models Using Receiver Operating Characteristic Curves,” Journal of Management Information Systems, 21(3), 2005, 249-280.