Osman Ozaltin

Assistant Professor of Personalized Medicine

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 Assistant 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.


Ph.D. 2011


University of Pittsburgh

MS 2007

Master of Science

University of Pittsburgh

BS 2005

Bachelor of Science

Bogazici University

Research Description

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.

Honors and Awards

  • ,


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.
Models for predicting the evolution of influenza to inform vaccine strain selection
Agor, J. K., & Ozaltin, O. Y. (2018), Human Vaccines & Immunotherapeutics.
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
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).
Note on Cournot competition under yield uncertainty
Jansen, M. C., & Ozaltin, O. Y. (2017), Manufacturing & Service Operations Management, 19(2), 305–308.
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), In 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), In 2017 winter simulation conference (wsc) (pp. 2881–2892).
Single-ratio fractional integer programs with stochastic right-hand sides
Zhang, J., & Ozaltin, O. Y. (2017), IISE Transactions, 49(6), 579–592.
A scalable bounding method for multistage stochastic programs
Sandikci, B., & Ozaltin, O. Y. (2017), SIAM Journal on Optimization, 27(3), 1772–1800.

View all publications via NC State Libraries