Kazim Topuz PhD

Assistant Professor of Operations Management & Business Analytics Collins College of Business
School of Finance, Operations Management and International Business
Curriculum Vitae [PDF]


Dr. Kazim Topuz is an Assistant Professor of Operations Management and Business Analytics in the School of Finance, Operations Management and International Business in the Collins College of Business at the Tulsa University (TU). Prior to joining Collins College of Business, he taught at the Division of Management Information Systems in the Price College of Business at the University of Oklahoma (OU) as a lecturer, and he worked for the Center for Health Systems Innovation at Oklahoma State University (OSU) as a Research Fellow. In addition to his doctorate in philosophy (Ph.D.) from the Wichita State University (WSU), Dr. Topuz holds masters` degrees in Information Systems Engineering from Lehigh University, and Industrial and Systems Engineering from Rutgers University.

Ph.D., Wichita State University
M.S., Rutgers University
M.S., Lehigh University
B.S., Yildiz Technical Univeristy

Business/Data Analytics, Machine Learning, Healthcare Analytics, Predictive and Prescriptive Analytics, Bayesian Belief Networks, Decision Support Systems, Probabilistic Graphical Models

Business Analytics, Data Systems, Business Data Analysis, Data Science and Analytics, Operations Management, R and Python Programming for Data Science, Database Management

The following may be selected publications rather than a comprehensive list.

Journal Articles

Topuz, K., Uner, H., Oztekin, A., & Yildirim, M. (2018). Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network. Annals of Operations Research, 263(1-2), 479–499.

Rouyendegh, B., Topuz, K., Dag, A., & Oztekin, A. (2018). An AHP-IFT Integrated Model for Performance Evaluation of E-Commerce Web Sites. Information Systems Frontiers, 1–11.

Topuz, K., Zengul, F., Dag, A., Almehmi, A., & Yildirim, M. (2018). Predicting graft survival among kidney transplant recipients: A Bayesian decision support model. Decision Support Systems, 106, 97–109.

Delen, D., Tomak, L., Topuz, K., & Eryarsoy, E. (2017). Investigating injury severity risk factors in automobile crashes with predictive analytics and sensitivity analysis methods. Journal of Transport and Health, 4, 118–131

Dag, A., Topuz, K., Oztekin, A., Bulur, S., & Megahed, F. (2016). A probabilistic data-driven framework for scoring the preoperative recipient-donor heart transplant survival. Decision Support Systems, 86, 1–12.

Maqbal, M., & Topuz, K. (2019). Enterprise Social Media: Combating Techno-stress and Turnover. Internet Research.

Delen, D., & Topuz, K. (2019). Probabilistic Decision Support Model for Predicting Freshmen Student Attrition. European Journal of Operations Research (EJOR) .

Topuz, K. (2019). A Unifying Framework to Assess Continuity of Care. Management Science.

Topuz, K. (2019). Probabilistic Model for Predicting the Risk Level of Graft- Donor Matching for Liver Transplantation. Medical Decision Making.

Conference Proceeding

Luxhøj, J., & Topuz, K. (2013). Probabilistic causal modeling of runway incursion (RI) safety risk. In IIE Annual Conference and Expo 2013 (pp. 4086–4095).

American Medical Informatics Association
Decision Science Institute