PhD, University of Toronto, 2015
MS, University of Toronto, 2010
BS, Korea University, 2008
Nadi, S., Lee, T., & Prokopyev, O.A. (2025). The inverse optimal value problem for linear fractional programming. OPERATIONS RESEARCH LETTERS, 59, 107251.Elsevier. doi: 10.1016/j.orl.2025.107251.
Mildebrath, D., Lee, T., Sinha, S., J., A., & Gaber, A.O. (2024). Characterizing Rational Transplant Program Response to Outcome-Based Regulation. OPERATIONS RESEARCH, 72(4), 1421-1437.Institute for Operations Research and the Management Sciences (INFORMS). doi: 10.1287/opre.2018.0721.
Ajayi, T., Lee, T., Schaefer, A.J., Lee, T. (2023). A note on the implications of approximate submodularity in discrete optimization. Optimization Letters, 17(1), 1-26.
Dorali, P., Shahmoradi, Z., Weng, C.Y., & Lee, T. (2023). Cost-effectiveness Analysis of a Personalized, Teleretinal-Inclusive Screening Policy for Diabetic Retinopathy via Markov Modeling. Ophthalmology Retina, 7(6), 532-542.Elsevier. doi: 10.1016/j.oret.2023.01.001.
Ajayi, T., Lee, T., & Schaefer, A.J. (2022). Objective Selection for Cancer Treatment: An Inverse Optimization Approach. Operations Research, 70(3), 1-22.
Shahmoradi, Z., & Lee, T. (2022). Quantile Inverse Optimization: Improving Stability in Inverse Linear Programming. Operations Research, 70(4), 2538-2562.
Shahmoradi, Z., & Lee, T. (2022). Optimality-based clustering: An inverse optimization approach. Operations Research Letters, 50(2), 205-212.Elsevier. doi: 10.1016/j.orl.2021.12.012.
Babier, A., Chan, T.C.Y., Lee, T., Mahmood, R., & Terekhov, D. (2021). An Ensemble Learning Framework for Model Fitting and Evaluation in Inverse Linear Optimization. INFORMS Journal on Optimization, 3(2), 119-138.Institute for Operations Research and the Management Sciences (INFORMS). doi: 10.1287/ijoo.2019.0045.
Chan, T.C.Y., Lee, T., & Terekhov, D. (2019). nverse Optimization: Closed-Form Solutions, Geometry, and Goodness of Fit. Management Science, 1115-1135. doi: 10.1287/mnsc.2017.2992.
Chan, T.C.Y., & Lee, T. (2018). Trade-off preservation in inverse multi-objective convex optimization. European Journal of Operational Research, 270(1), 25-39.Elsevier. doi: 10.1016/j.ejor.2018.02.045.
Ghobadi, K., Lee, T., Mahmoudzadeh, H., & Terekhov, D. (2018). Robust inverse optimization. Operations Research Letters, 46(3), 339-344.Elsevier. doi: 10.1016/j.orl.2018.03.007.
Tavashoglu, O., Lee, T., Valeva, S., & Schaefer, A.J. (2018). On the structure of the inverse-feasible region of a linear program. Operations Research Letters, 46(1), 147-152.Elsevier. doi: 10.1016/j.orl.2017.12.004.
Boutilier, J.J., Lee, T., Craig, T., Sharpe, M.B., & Chan, T.C.Y. (2015). Models for predicting objective function weights in prostate cancer IMRT. Medical Physics, 42(4), 1586-1595.Wiley. doi: 10.1118/1.4914140.
Chan, T.C.Y., Craig, T., Lee, T., & Sharpe, M.B. (2014). Generalized Inverse Multiobjective Optimization with Application to Cancer Therapy. Operations Research, 62(3), 680-695.Institute for Operations Research and the Management Sciences (INFORMS). doi: 10.1287/opre.2014.1267.
Lee, T., Hammad, M., Chan, T.C.Y., Craig, T., & Sharpe, M.B. (2013). Predicting objective function weights from patient anatomy in prostate IMRT treatment planning. Medical Physics, 40(12), 121706.Wiley. doi: 10.1118/1.4828841.