Mumtaz Karatas, Ph.D., is a tenured Associate Professor and Interim Chair of the Department of Biomedical, Industrial and Human Factors Engineering at Wright State University. He leads the Decision Analytics and Optimization Laboratory, where his research integrates operations research, artificial intelligence, and data analytics to improve decisions in complex engineering and organizational systems. Since joining Wright State in 2024, he has also served in program leadership roles in Industrial and Human Factors Engineering and as a focus area chair in the interdisciplinary Ph.D. in Engineering program.

Dr. Karatas earned his B.Sc. in Industrial Engineering from the Turkish Naval Academy in 2001, his M.Sc. in Industrial and Operations Engineering from the University of Michigan in 2006, and his Ph.D. in Industrial Engineering from Kocaeli University in 2012. He held visiting doctoral and postdoctoral research appointments in the Department of Operations Research at the Naval Postgraduate School. Before joining Wright State, he served for ten years as a faculty member at the Turkish Naval Academy, including leadership appointments as department chair, vice dean, and director of the Operations Research Division. His professional experience also includes six years as an operations research analyst for the Turkish Navy and service as Director of the Modeling and Simulation Department at the Navy Research Center.

His research develops mathematical models, algorithms, and decision-support methods for systems in which resources, information, and operational capacity are limited. His methodological interests include network and combinatorial optimization, mixed-integer programming, stochastic and robust optimization, multiobjective decision-making, simulation, and the integration of machine learning with optimization. A central theme is connecting predictive analytics—understanding what is likely to happen—with prescriptive analytics—determining what actions to take.

Dr. Karatas applies these methods to supply-chain design and resilience, transportation and logistics, advanced manufacturing, healthcare operations, autonomous systems, energy infrastructure, and defense planning. His work addresses facility location and capacity planning, integrated location–inventory–routing decisions, sensor-network design, emergency response, and the coordination of unmanned aerial and maritime vehicles. Recent research includes advanced air mobility and vertiport planning, sustainable logistics network transitions, cooperative human and machine learning for manufacturing, healthcare digital twins, and cooperative decision-making under limited information and communication.

Dr. Karatas has published more than 70 peer-reviewed journal articles and presented his research at more than 30 international conferences. His publications appear in journals including European Journal of Operational Research, Omega, Computers & Operations Research, Computers & Industrial Engineering, Naval Research Logistics, Annals of Operations Research, Applied Soft Computing, Expert Systems with Applications, Applied Energy, IEEE Transactions on Intelligent Transportation Systems, and IEEE Transactions on Evolutionary Computation. His scholarship spans both methodological advances in optimization and applications addressing practical engineering and societal challenges.

His teaching covers undergraduate and graduate courses in operations research, mathematical modeling, optimization, machine learning, decision analysis, production and service systems, and research methods. He advises doctoral and master’s students and has supervised more than 50 undergraduate capstone, senior-design, and independent-study projects. His students participate in funded research, develop computational and analytical skills, and disseminate their work through journal publications and conference presentations. In 2025, his doctoral student Zahra Zare earned first place in the Supply Chain and Logistics Competition and second place in the Graduate Student Paper Competition at the North American Industrial Engineering and Operations Management Conference.

Dr. Karatas serves as an Associate Editor of Healthcare Analytics and the Journal of Data, Information and Management. His editorial board service includes Applied Soft Computing, Journal of Business Analytics, Drones, International Journal of Applied Management Science, and Journal of Naval Science and Engineering. He has also served as a guest editor for Expert Systems, Micromachines, Drones, Frontiers in Public Health, and Frontiers in Computational Neuroscience. He is co-editor of Operations Research for Military Organizations, published by IGI Global in 2018. His professional service includes more than 400 manuscript reviews for over 80 journals, evaluation of more than 30 research proposals, and conference leadership as a track chair, session chair, and organizing or technical program committee member.

Dr. Karatas has been recognized in the Stanford University/Elsevier Top 2% Scientists List, achieving a ranking of #259 out of 30,698 authors in the field of “Operations Research” for 2025, placing him in the top 0.8%.

Selected publications illustrating the breadth and current direction of his research include:

1. Zare, Z., Zheng, Y.-J., and Karatas, M. (2026). A multi-period optimization model for net-zero logistics network transition planning. Supply Chain Analytics, 100231.

2. Cheng, Y.-Y., Feng, Y.-A., Ling, H.-F., Karatas, M., Chen, S., and Zheng, Y.-J. (2026). Relief vehicle routing considering driver state evolution in harsh environments: A maximum likelihood deep reinforcement learning approach. IEEE Transactions on Intelligent Transportation Systems.

3. Zare, Z., Eriskin, L., and Karatas, M. (2026). Sustainable and smart urban air mobility: A semi-desirable hub location and sizing approach for vertiport planning. Computers & Industrial Engineering, 112027.

4. Song, Q., Chen, X.-Y., Zhang, P.-W., Karatas, M., Sheng, W.-G., and Zheng, Y.-J. (2026). Nurse rostering constrained by physiological-psychological state evolution. IEEE Transactions on Evolutionary Computation.

5. Yakici, E., Eriskin, L., Karatas, M., and Karasakal, O. (2026). Optimization of fleet search on network of regions. Computers & Operations Research, 107394.

6. Misic, A. S., Karatas, M., and Dasci, A. (2025). Optimal sizing and location of energy storage systems for transmission grids connected to wind farms. Omega, 103301.

7. Bozkaya-Aras, E., Onel, T., Eriskin, L., and Karatas, M. (2025). Intelligent human activity recognition for healthcare digital twin. Internet of Things, 101497.

8. Eriskin, L., and Karatas, M. (2024). Applying robust optimization to the shelter location–allocation problem: A case study for Istanbul. Annals of Operations Research, 339(3), 1589–1635.

9. Karatas, M., and Eriskin, L. (2023). Linear and piecewise linear formulations for a hierarchical facility location and sizing problem. Omega, 118, 102850.

10. Karatas, M., and Eriskin, L. (2021). The minimal covering location and sizing problem in the presence of gradual cooperative coverage. European Journal of Operational Research, 295(3), 838–856.

11. Wu, C.-X., Liao, M.-H., Karatas, M., Chen, S.-Y., and Zheng, Y.-J. (2020). Real-time neural network scheduling of emergency medical mask production during COVID-19. Applied Soft Computing, 97, 106790. Best Paper Award, 2022.

12. Craparo, E., and Karatas, M. (2020). Optimal source placement for point coverage in active multistatic sonar networks. Naval Research Logistics, 67(1), 63–74.

Additional publications and citation information are available through his Google Scholar profile.