Taewoo Lee
Assistant Professor
Industrial Engineering
University of Pittsburgh
email: taewoo.lee [at] pitt [dot] edu
CV: PDF
Welcome to my website!
I am an Assistant Professor of Industrial Engineering at the University of Pittsburgh. My general research interests are in the applications of optimization techniques such as inverse optimization, robust optimization, and dynamic programming to healthcare operations and medical decision making. Specific application areas of interest include radiation therapy, organ transplantation, and screening for diabetic complications. I am also affiliated with the Department of Computational Applied Mathematics and Operations Research (CMOR) at Rice University. I received my PhD in 2015 in operations research from the University of Toronto.
Research Interests
- Inverse optimization and statistical machine learning
- Knowledge-based trade-off analysis and optimization in cancer treatment design
- Designing screening and outreach care programs for chronic diseases
- Policy making for organ transplantation centers
Recent News
- New paper: "Characterizing rational transplant program response to outcome-based regulation," Operations Research
- Thank you to NSF (CMMI-2321399) for supporting our project on integrating personalized treatment with healthcare resource planning
- New Book Chapter available: "Inverse Optimization," Encyclopedia of Optimization
- New Book Chapter available: "Inverse Integer Optimization," Encyclopedia of Optimization
- New Book Chapter available: "Data-Driven Inverse Optimization," Encyclopedia of Optimization
- New Paper: "Cost-Effectiveness Analysis of a Personalized, Teleretinal-Inclusive Screening Policy for Diabetic Retinopathy via Markov Modeling," Ophthalmology Retina
- New paper: "Utilizing simulation to update routine diabetic retinopathy screening policies," the Proceedings of the 2022 Winter Simulation Conference
- Thank you to NSF (CMMI-2243071) for supporting our project on optimal design of a teleretinal screening program in Western Pennsylvania
- New paper: "A Note on the Implications of Approximate Submodularity in Discrete Optimization," Optimization Letters
- New paper: "Optimality-Based Clustering," Operations Research Letters
- New paper: "Objective selection for cancer treatment: An inverse optimization approach," Operations Research
- New paper: "Quantile Inverse Optimization: Improving Stability in Inverse Linear Programming," Operations Research
- New paper: "An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization," INFORMS Journal on Optimization
- Thank you to CMS for supporting our project on diabetic eye disease management and resource allocation for minority patients in Harris County
- Thank you to NSF (CMMI-1826297) for supporting our project on optimal design of a telehealth screening program for at-risk patients
- New paper: "Inverse Optimization: Closed-Form Solutions, Geometry, and Goodness of Fit" at Management Science
- Thank you to NSF for supporting our project: "Optimal Performance Incentives for Organ Transplantation Centers"