Osman Ozaltin
Bio
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.
Education
Ph.D Ph.D University of Pittsburgh 2011
MS Master of Science in Industrial Engineering University of Pittsburgh 2007
BS Bachelor of Science Bogazici University 2005
Area(s) of Expertise
Osman Ozaltin’s research interests include 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, and optimization of parameters in bioinformatics models and decision making under uncertainty.
Publications
- Reducing Manual Labeling Effort in Imbalanced Data Sets: Active Learning for Detecting Illicit Massage Business Reviews , Operations Research (2026)
- Improving deceased donor kidney utilization: predicting risk of nonuse with interpretable models , Frontiers in Artificial Intelligence (2025)
- Modeling Social Influence on Covid-19 Vaccination Uptake Within an Agent-Based Model , (2025)
- Incorporating Face Mask Usage in Agent-Based Models Using Personal Beliefs and Perceptions: An Application of the Health Belief Model , 2024 WINTER SIMULATION CONFERENCE, WSC (2024)
- Risk score models for urinary tract infection hospitalization , PLoS ONE (2024)
- Solving a class of two-stage stochastic nonlinear integer programs using value functions , Journal of Global Optimization (2024)
- Temporal pattern mining for knowledge discovery in the early prediction of septic shock , Pattern Recognition (2024)
- Detecting Human Trafficking: Automated Classification of Online Customer Reviews of Massage Businesses , Manufacturing & Service Operations Management (2023)
- Quantifying association and disparities between diabetes complications and COVID-19 outcomes: A retrospective study using electronic health records , PLoS ONE (2023)
- Coordination of manufacturing and engineering activities during product transitions , Naval Research Logistics (NRL) (2022)