Gedas Adomavicius
Carolyn I. Anderson Chair in Business Education Excellence
and Professor of Information and Decision Sciences

CONTACT INFORMATION
Department of Information and Decision Sciences
Carlson School of Management
University of Minnesota
Address:   321 19th Avenue South, Minneapolis, MN 55455
Phone:   (612) 625-9504
Fax:   (612) 626-1316
Email:   gedas [at] umn [dot] edu
URL:   http://ids.csom.umn.edu/faculty/gedas/

RESEARCH INTERESTS

General interests:
TEACHING

MBA courses: MS in Business Analytics courses Undergraduate courses: PhD courses: Executive education:
RESEARCH GRANTS

External Research Grants: My research has also been funded from various internal sources at the University of Minnesota, including:
SELECTED PRESENTATIONS

Tutorial presentations:
PUBLICATIONS

Journal publications:
  1. M. Yang, G. Adomavicius, G. Burtch, and Y. Ren. "Mind the Gap: Accounting for Measurement Error and Misclassification in Variables Generated via Data Mining." Information Systems Research, forthcoming.
  2. G. Adomavicius, J. Bockstedt, S. Curley, and J. Zhang. "Effects of Online Recommendations on Consumers’ Willingness to Pay." Information Systems Research, forthcoming.
  3. J. Wolfson, D. Vock, S. Bandyopadhyay, T. Kottke, G. Vazquez Benitez, P. Johnson, G. Adomavicius, and P. O’Connor. "Use and Customization of Risk Scores for Predicting Cardiovascular Events Using Electronic Health Record Data." Journal of the American Heart Association, vol. 6, no. 4, April 2017.
  4. M. Bichler, Z. Hao, and G. Adomavicius. "Coalition-Based Pricing in Ascending Combinatorial Auctions." Information Systems Research, vol. 28, no. 1, March 2017.
  5. A. Ermagun, Y. Fan, J. Wolfson, G. Adomavicius, and K. Das. "Real-Time Trip Purpose Prediction Using Online Location-Based Search and Discovery Services." Transportation Research Part C: Emerging Technologies, vol. 77, April 2017.
  6. D.M. Vock, J. Wolfson, S. Bandyopadhyay, G. Adomavicius, P.E. Johnson, G. Vazquez-Benitez, and P.J. O’Connor. "Adapting machine learning techniques to censored time-to-event health record data: A general-purpose approach using inverse probability of censoring weighting." Journal of Biomedical Informatics, vol. 61, June 2016.
  7. G. Adomavicius and J. Zhang. "Classification, Ranking, and Top-K Stability of Recommendation Algorithms." INFORMS Journal on Computing, vol. 28, no. 1, 2016.
  8. J. Wolfson, S. Bandyopadhyay, M. Elidrisi, G. Vazquez-Benitez, D. Vock, D. Musgrove, G. Adomavicius, P. Johnson, and P. O’Connor. "A Naïve Bayes Machine Learning Approach to Risk Prediction Using Censored, Time-to-Event Data." Statistics in Medicine, vol. 34, no. 21, 2015.
  9. S. Bandyopadhyay, J. Wolfson, D.M. Vock, G. Vazquez-Benitez, G. Adomavicius, M. Elidrisi, P.E. Johnson, P.J. O'Connor. "Data mining for censored time-to-event data: A Bayesian network model for predicting cardiovascular risk from electronic health record data." Data Mining and Knowledge Discovery, vol. 29, no. 4, July 2015.
  10. G. Adomavicius and J. Zhang. "Improving Stability of Recommender Systems: A Meta-Algorithmic Approach." IEEE Transactions on Knowledge and Data Engineering, vol. 27, no. 6, June 2015.
  11. G. Adomavicius, J. Bockstedt, and S. Curley. "Bundling Effects on Variety Seeking for Digital Information Goods." Journal of Management Information Systems, vol. 31, no. 4, 2015.
  12. G. Meyer, G. Adomavicius, P. Johnson, M. Elidrisi, W. Rush, J. Sperl-Hillen, and P. O'Connor. "A Machine Learning Approach to Improving Dynamic Decision Making." Information Systems Research, vol. 25, no. 2, June 2014.
  13. G. Adomavicius and Y. Kwon. "Optimization-Based Approaches for Maximizing Aggregate Recommendation Diversity." INFORMS Journal on Computing, vol. 26, no. 2, Spring 2014.
  14. G. Adomavicius, J. Bockstedt, S. Curley, and J. Zhang. "Do Recommender Systems Manipulate Consumer Preferences? A Study of Anchoring Effects." Information Systems Research, vol. 24, no. 4, December 2013.
  15. G. Adomavicius, S. Curley, A. Gupta, and P. Sanyal. "User Acceptance of Complex Electronic Market Mechanisms: Role of Information Feedback." Journal of Operations Management, vol. 31, no. 6, September 2013.
  16. G. Adomavicius, S. Curley, A. Gupta, and P. Sanyal. "Impact of Information Feedback in Continuous Combinatorial Auctions: An Experimental Study of Economic Performance." MIS Quarterly, vol. 37, no. 1, March 2013.
  17. G. Adomavicius and J. Zhang. "Stability of Recommendation Algorithms." ACM Transactions on Information Systems, vol. 30, no. 4, November 2012.
  18. G. Adomavicius, J. Bockstedt, and A. Gupta. "Modeling Supply-Side Dynamics of IT Components, Products, and Infrastructure: An Empirical Analysis Using Vector Autoregression." Information Systems Research, vol. 23, no. 2, June 2012.
  19. G. Adomavicius and Y. Kwon. "Improving Aggregate Recommendation Diversity Using Ranking-Based Techniques." IEEE Transactions on Knowledge and Data Engineering, vol. 24, no. 5, May 2012.
  20. G. Adomavicius, S. Curley, A. Gupta, and P. Sanyal. "Effect of Information Feedback on Bidder Behavior in Continuous Combinatorial Auctions." Management Science, vol. 58, no. 4, April 2012.
  21. G. Adomavicius, A. Gupta, and P. Sanyal. "Effect of Information Feedback on the Outcomes and Dynamics of Multisourcing Multiattribute Procurement Auctions." Journal of Management Information Systems, vol. 28, no. 4, Spring 2012.
  22. G. Adomavicius and J. Zhang. "Impact of Data Characteristics on Recommender Systems Performance." ACM Transactions on Management Information Systems, vol. 3, no. 1, April 2012.
  23. G. Adomavicius, B. Mobasher, F. Ricci, and A. Tuzhilin. "Context-Aware Recommender Systems." AI Magazine, vol. 32, no. 3, 2011.
  24. G. Adomavicius, A. Tuzhilin, and R. Zheng. "REQUEST: A Query Language for Customizing Recommendations." Information Systems Research, vol. 22, no. 1, March 2011. [Working paper version: PDF ]
  25. G. Adomavicius, A. Gupta, and D. Zhdanov. "Designing Intelligent Software Agents for Auctions with Limited Information Feedback." Information Systems Research, vol. 20, no. 4, December 2009.
  26. G. Adomavicius, J. Bockstedt, A. Gupta, and R. Kauffman. "Making Sense of Technology Trends in the IT Landscape: A Design Science Approach." MIS Quarterly, vol. 32, no. 4, December 2008.
  27. G. Adomavicius, J. Bockstedt, A. Gupta, and R. Kauffman. "Understanding Evolution in Technology Ecosystems." Communications of the ACM, vol. 51, no. 10, October 2008.
  28. G. Adomavicius and J. Bockstedt. "C-TREND: Temporal Cluster Graphs for Identifying and Visualizing Trends in Multi-Attribute Transactional Data." IEEE Transactions on Knowledge and Data Engineering, vol. 20, no. 6, June 2008.
  29. G. Adomavicius and Y. Kwon. "New Recommendation Techniques for Multi-Criteria Rating Systems." IEEE Intelligent Systems, vol. 22, no. 3, May/June 2007.
  30. G. Adomavicius, J. Bockstedt, A. Gupta, and R. Kauffman. "Technology Roles and Paths of Influence in an Ecosystem Model of Technology Evolution." Information Technology and Management, vol. 8, no. 2, June 2007.
  31. G. Adomavicius and A. Tuzhilin. "Validation Sequence Optimization: A Theoretical Approach." INFORMS Journal on Computing, vol. 19, no. 2, Spring 2007. [PDF, appendix]
  32. G. Adomavicius and A. Tuzhilin. "Personalization Technologies: A Process-Oriented Perspective." Communications of the ACM, vol. 48, no. 10, October 2005.
  33. G. Adomavicius and A. Gupta. "Towards Comprehensive Real-Time Bidder Support in Iterative Combinatorial Auctions." Information Systems Research, vol. 16, no. 2, June 2005. [ PDF ]
  34. G. Adomavicius and A. Tuzhilin. "Towards the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions." IEEE Transactions on Knowledge and Data Engineering, vol. 17, no. 6, June 2005. [Working paper version: PDF ]
  35. G. Adomavicius, R. Sankaranarayanan, S. Sen, and A. Tuzhilin. "Incorporating Contextual Information in Recommender Systems Using a Multidimensional Approach." ACM Transactions on Information Systems, vol. 23, no. 1, January 2005. [Working paper version: PDF ]
  36. G. Adomavicius and A. Tuzhilin. "An Architecture of e-Butler: A Consumer-Centric Online Personalization System." International Journal of Computational Intelligence and Applications, vol. 2, no. 3, September 2002.
  37. G. Adomavicius and A. Tuzhilin. "Using Data Mining Methods to Build Customer Profiles." IEEE Computer, vol. 34, no. 2, February 2001.
  38. G. Adomavicius and A. Tuzhilin. "Expert-Driven Validation of Rule-Based User Models in Personalization Applications." Data Mining and Knowledge Discovery, vol. 5, nos. 1/2, January/April 2001. [Working paper version: PDF ]

Last modified: January 15, 2015