Gregory  Ramsey

Assistant Professor
Ph.D., University of Minnesota, 2010



Gregory Ramsey is an Assistant Professor in the Information Science and Systems Department in the Earl G. Graves School of Business and Management. Prof. Ramsey received a B.S. in Electrical Engineering from Duke University, an M.S. in Electrical Engineering from Georgia Institute of Technology, an MSIA from the Tepper School of Business at Carnegie Mellon University, and a Ph.D. in Business Administration (Information and Decision Sciences) from the Carlson School of Management at the University of Minnesota. He has completed a post-doctoral fellowship at the Stern School of Business at New York University.

Research Interests

  • Decision making
  • Process characterization
  • Health Care Analytics

Recent Papers & Publications

Ramsey, G. W. (2014).  Evaluating Policies using Agent-based Simulations: Investigating Policies for Continuity of Care.   International Journal of Simulation and Process Modelling, 9 (4), 255-269.  

Ramsey, G. & Bapna, S. (2014).  A Technique to Exploit Free-Form Notes to Predict Customer Churn.   International Journal of Computational Models and Algorithms in Medicine, 4 (4), 16.  

Ramsey, G. & Bapna, S. (2014).  A European Loyalty Program: Examining Purchase Behavior to Predict Likelihood of Retaining Individual Customers.   International Journal of Business and Commerce, 3 (9), 27-35.  

Ramsey, G. W., Johnson, P. E., O'Connor, P. J., Sperl-Hillen, J. M., Rush, W. A., George Biltz (2014).  Examining Failure in a Dynamic Decision Environment: Strategies for Treating Patients with a Chronic Disease.   Annals of Information Systems, 19, 1-15.   

Ramsey, G., Johnson, P., O'Connor, P., Sperl-Hillen, J., Rush, W., George Biltz, (2010). Identifying Physician Decision Strategies for Treating Patients with Type 2 Diabetes. American Diabetes Association 70th Scientific Session, Orlando, Florida.

Ramsey, G., Johnson, P., O'Connor, P., Sperl-Hillen, J., Rush, W., George Biltz, (2010). Computational Models for Investigating Success and Failure in Treating Patients with Type 2 Diabetes. 5th INFORMS Workshop on Data Mining and Health Informatics, Arlington, Virginia.

Ramsey, G., Johnson, P., O'Connor, P., Sperl-Hillen, J., & Rush, W. (2010). Using Functional Data Analysis to Identify Physician Decision Strategies which Lead to Better Type 2 Diabetes Patient Outcomes. 1st ACM International Conference on Health Informatics, Austin, Texas.

McCabe, R., Adomavicius, G., Johnson, P., Ramsey, G., Rund, E., William Rush, Patrick O'Connor, JoAnn Sperl-Hillen, (2008). "Using Data Mining to Predict Errors in Chronic Disease Care", Advances in Patient Safety: New Directions and Alternative Approaches. Rockville: Agency for Healthcare Research and Quality.