Currently I am a Ph.D. student in the Risk Analytics and Optimization Lab at École polytechnique fédérale de Lausanne (EPFL) in Switzerland.
My research is focused on machine learning theory, and I am fortunate to be advised by Daniel Kuhn. In 2018, I obtained my Bachelor of Science degree in Electrical and Electronics Engineering from the Middle East Technical University.
My research interests center around decision-making under uncertainty, large-scale stochastic optimization, and statistical inference. I am particularly interested in exploring algorithmic fairness and robustness and their applications in operations management, control, and machine learning. My work has implications for the development and deployment of responsible AI systems.
News:
I am hiring a postdoctoral principal researcher! Please apply here if you are interested in!
🎉 I will join the University of Chicago Booth School of Business as an Assistant Professor of Operations Management in September 2024.
Our paper "Distributionally Robust Linear Quadratic Control" is accepted at NeruIPS 2023 as a spotlight!
Our paper "Distributionally Robust Linear Quadratic Control" is selected as a finalist for the "George Nicholson Student Paper Competition", INFORMS 2023!
At the INFORMS Annual Meeting (October 15-18, 2023), I'm hosting a session titled "Structuring the Ambiguous: New Perspectives on Distributionally Robust Learning". During this session, I will present our latest paper, "Pessimistic Estimates and Optimistic Decisions for Bandits".
Contact
bahar [dot] taskesen [at] epfl [dot] ch
