Associate Professor of Personalized Medicine
- 368 Daniels Hall
Osman Ozaltin joined North Carolina State University in August 2013 as a Chancellor’s Faculty Excellence Program cluster hire in Personalized Medicine. He is an Associate Professor in the Edward P. Fitts Department of Industrial and Systems Engineering and part of the Healthcare Systems Engineering group. His research interests span theoretical, computational, and applied aspects of mathematical programming, focusing on multilevel stochastic optimization problems arising in public health policy making, personalized medical decision-making, and healthcare delivery. He is also interested in developing efficient algorithms for large-scale combinatorial problems in bioinformatics. His methods include integer programming, combinatorial optimization, stochastic programming, bilevel programming, quadratic programming, and decomposition algorithms.
Prior to joining NC State, Ozaltin was an Assistant Professor of Management Sciences at the University of Waterloo, Canada. His publications appeared in top academic journals including Operations Research and Mathematical Programming. He received the distinguished Institute of Industrial Engineers Best Dissertation Award in 2013 for his work to optimize the annual influenza vaccine design. Ozaltin’s formal education began with a BS in Industrial Engineering from Bogazici University in Istanbul, Turkey. He then received his MS and Ph.D. in Industrial Engineering from the University of Pittsburgh.
University of Pittsburgh
Master of Science
University of Pittsburgh
Bachelor of Science
Optimization of service systems, particularly in health care; vaccine design and supply chain; public health policy making, public service delivery, disease management and treatment scheduling, optimization of parameters in bioinformatics models, decision making under uncertainty.
- Feature selection for classification models via bilevel optimization
- Agor, J., & Ozaltin, O. Y. (2019), COMPUTERS & OPERATIONS RESEARCH, 106, 156–168. https://doi.org/10.1016/j.cor.2018.05.005
- Tollgate-based progression pathways of ALS patients
- Dalgic, O. O., Erenay, F. S., Pasupathy, K. S., Ozaltin, O. Y., & Crum, B. A. (2019), JOURNAL OF NEUROLOGY, 266(3), 755–765. https://doi.org/10.1007/s00415-019-09199-y
- Ambulance redeployment and dispatching under uncertainty with personnel workload limitations
- Enayati, S., Ozaltin, O. Y., Mayorga, M. E., & Saydam, C. (2018), IISE Transactions, 50(9), 777–788. https://doi.org/10.1080/24725854.2018.1446105
- Models for predicting the evolution of influenza to inform vaccine strain selection
- Agor, J. K., & Ozaltin, O. Y. (2018). [Review of , ]. Human Vaccines & Immunotherapeutics, 14(3), 678–683. https://doi.org/10.1080/21645515.2017.1423152
- Optimal production in a competitive market under yield uncertainty
- Jansen, M. C., & Ozaltin, O. Y. (2018), OPTIMIZATION LETTERS, 12(7), 1487–1502. https://doi.org/10.1007/s11590-018-1288-0
- A scalable bounding method for multistage stochastic programs
- Sandikci, B., & Ozaltin, O. Y. (2017), SIAM Journal on Optimization, 27(3), 1772–1800. https://doi.org/10.1137/16m1075594
- Deriving effective vaccine allocation strategies for pandemic influenza: Comparison of an agent-based simulation and a compartmental model
- Dalgic, O. O., Ozaltin, O. Y., Ciccotelli, W. A., & Erenay, F. S. (2017), PLoS One, 12(2). https://doi.org/10.1371/journal.pone.0172261
- Note on Cournot competition under yield uncertainty
- Jansen, M. C., & Ozaltin, O. Y. (2017), Manufacturing & Service Operations Management, 19(2), 305–308. https://doi.org/10.1287/msom.2016.0610
- Predicting future states in dota 2 using value-split models of time series attribute data
- Cleghern, Z., Lahiri, S., Ozaltin, O., & Roberts, D. L. (2017), Proceedings of the 12th International Conference on the Foundations of Digital Games (FDG'17).
- Simulating triage of patients into an internal medicine department to validate the use of an optimization-based workload score
- Agor, J., McKenzie, K., Mayorga, M. E., Ozaltin, O., Parikh, R. S., & Huddleston, J. (2017), 2017 winter simulation conference (wsc), 2881–2892. https://doi.org/10.1109/wsc.2017.8248011