About
Kazim Topuz is associate professor of business analytics and operations management in the Collins College of Business at The University of Tulsa, where he serves as graduate director of the Master of Science in Business Analytics program and holds the J. Bradley Oxley Endowed Chair in Business Analytics. He is also founder of Mind Your AI, a firm focused on AI strategy, consulting, applied research and business solutions.
Originally from Turkey, Topuz values curiosity, hard work and treating people with respect—principles that continue to shape how he teaches, researches and collaborates.
Topuz earned a doctorate in industrial engineering from Wichita State University, where his research focused on data mining applications in healthcare. He also holds master’s degrees in information systems engineering from Lehigh University and industrial and systems engineering from Rutgers University.
His research focuses on explainable, trustworthy and prescriptive artificial intelligence, with applications in healthcare, mental health, transportation safety, education and other social systems. His work emphasizes developing models that not only predict outcomes but also provide actionable insights for decision-making.
Topuz has published research in leading journals, including the Journal of Management Information Systems, European Journal of Operational Research, Decision Support Systems, OMEGA, Annals of Operations Research and Information Systems Frontiers. He has served as a special issue editor for Decision Support Systems and Annals of Operations Research on topics related to explainable AI and interpretable machine learning.
As graduate director of the business analytics program, Topuz leads curriculum development, student advising, recruitment initiatives and program strategy. He also contributes to online MBA course development and AI-focused academic initiatives. He mentors students in applied research, analytics competitions and industry projects, including teams recognized in national innovation competitions.
His honors include the 2023 Institute of Industrial and Systems Engineers Gold Award, the 2022 Mayo Research Excellence Award and the Chapman Professorship Award. He is a member of the Institute for Operations Research and the Management Sciences, Decision Sciences Institute, American Medical Informatics Association and Institute of Industrial and Systems Engineers.
Awards & Honors
- Mayo Teaching Excellence Award, The University of Tulsa Collins College of Business, 2025
- IISE Gold Award, Institute of Industrial and Systems Engineers, 2023
- Mayo Research Excellence Award, The University of Tulsa, 2022
- Tau Beta Pi Teaching Excellence Award, The University of Tulsa, 2022, 2014, 2012
- Chapman Professorship Award, The University of Tulsa, 2020–2022
- Chemical Engineering Outstanding Teacher Award, Omega Chi Epsilon, Beta Psi Chapter, 2016
- Outstanding Doctoral-level Student Award, Wichita State University, 2016
- Industrial Engineering Honor Society Membership Award, Alpha Pi Mu
- Fellowship, Rutgers University
- Fellowship, Turkish Ministry of National Education
- First Place, National Case Study Competition, Turkey, 2007
- Top 0.1% Ranking, Academic Graduate Exam, Turkey, 2007
Education
- Ph.D., Wichita State University
- Dissertation: “Data Analytics Frameworks and Probabilistic Graphical Models in Healthcare”
- M.E., Lehigh University
- Dissertation: “Information Systems Engineering”
- M.S., Rutgers University
- Dissertation: “Industrial and Systems Engineering”
Research Interests & Areas of Expertise
- Designing interpretable and probabilistic AI models, including Bayesian belief networks, Markov models and graph-based approaches, integrated with machine learning for data-driven, decision-oriented analytics
- Advancing explainable, trustworthy and prescriptive AI with applications in healthcare, mental health, transportation safety, education, risk analytics and broader social systems
- Developing decision support systems and decision intelligence frameworks that not only predict outcomes but also provide transparent, actionable insights for real-world decision-making
