Kazim (Dr.K) Topuz
Endowed Chair in Business Analytics | Associate Professor, Operations Management & Business Analytics | Director, MSBA Program at TU | Founder, Mind Your AI | AI Solutions · Consulting · Strategy · Research
Kazim Topuz, Ph.D., is an Associate Professor of Business Analytics and Operations Management at the Collins College of Business at The University of Tulsa. He holds a Ph.D. in Industrial Engineering with a dissertation on Data Mining Applications in Healthcare from Wichita State University and master’s degrees in Information Systems Engineering from Lehigh University and Industrial and Systems Engineering from Rutgers University.
His work focuses on designing probabilistic graphical models, including Bayesian Belief Networks and Markov Networks, integrated with data mining techniques for data-driven decisions. His current research passion is explainable AI and its applications in healthcare, accident severity, student retention, and mental health.
Dr. Topuz’s work has been published in prestigious journals such as the European Journal of Operational Research, Decision Support Systems (DSS), OMEGA, and the Annals of Operations Research (ANOR), among others. He is an active member of INFORMS, the Decision Science Institute, the American Medical Informatics Association, and the Institute of Industrial and Systems Engineers (IISE).
- The path to force: An explainable AI approach to model pathways to human trafficking. Annals of Operations Research (2024).
- Evidence-based managerial decision-making with machine learning: The case of Bayesian inference in aviation incidents. Omega (2023).
- MDScan: A novel framework for mental disorder screening with an explainable and probabilistic reasoning. Artificial Intelligence in Medicine (2022).
- A probabilistic Bayesian inference model to investigate injury severity in automobile crashes. Decision Support Systems (2021).
- A novel diffusion-based model for estimating cases, and fatalities in epidemics: The case of COVID-19. Journal of Business Research (2021).
- Development of a Bayesian Belief Network-based DSS for predicting and understanding freshmen student attrition. European journal of operational research (2020).
- Enterprise social media: combating turnover in businesses. Internet Research (2020).
- An AHP-IFT integrated model for performance evaluation of E-commerce web sites. Information Systems Frontiers (2019).
- Predicting graft survival among kidney transplant recipients: A Bayesian decision support model. Decision Support Systems (2018).
- Predicting pediatric clinic no-shows: a decision analytic framework using elastic net and Bayesian belief network. Annals of Operations Research (2018).
- 2025 Mayo Teaching Excellence Award
- 2023 IISE Gold Award
- 2022 Mayo Research Excellence Award
- Chapman Professorship Award (2020-2022)
- Outstanding Doctoral-level Student Award at Wichita State University (2016)
- Industrial Engineering Honor Society Membership Award (Alpha Pi Mu)
- Fellowships from Rutgers University and the Turkish Ministry of National Education
- First place in a national case study competition in Turkey (2007)
- Ranked in the top 0.1% among 500,000 university graduates in the Academic Graduate Exam in Turkey
Apart from analytics, Kazim enjoys photography, pickleball, traveling, and gardening. He is actively involved in serving communities such as refugees, minorities, and the underprivileged through volunteerism.