Gregory  Ramsey

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

 

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Biography
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.