Tianyu Wang
 |
To be uncertain is uncomfortable, but to be certain is ridiculous. -- Goethe |
at Lake 22, WA, USA (July 1, 2023)
About me
I am a third-year PhD student in the Department of Industrial Engineering and Operations Research at Columbia University, where I am co-advised by Professor Garud Iyengar and Henry Lam. I also work closely with Hongseok Namkoong. Previously, I obtained a B.E. in Information Systems and B.S. in Mathematics both from Tsinghua University in 2021.
My research lies at the interface of stochastic optimization and machine learning. I develop reliable methods for data-driven optimization problems with theoretical performance guarantees and practical uses. My current research aims at explaining and understanding the performance of algorithms to attain efficient decision trade-offs under uncertain environments.
Education
Ph.D. in Operations Research, Columbia University, Aug. 2021 - Present
M.S. in Operations Research, Columbia University, Aug. 2021 - Jun. 2022
B.S. in Pure and Applied Mathematics, Tsinghua University, Aug. 2018 - Jun. 2021
B.E. in Information Management and Information Systems, Tsinghua University, Aug. 2017 - Jun. 2021
Exchange Program, National University of Singapore, Jul. 2019 - Dec. 2019
Research Interests
Data-Driven Decision-making (Methodology): robust models against distribution shifts, conditional stochastic optimization.
Trustworthy Machine Learning (Application): robustness, explainability and their interplay in real operations problems.