I am a PhD candidate in Electrical Engineering at Caltech, advised by Prof. Babak Hassibi. My research is broadly centered on the interplay between control theory, optimization, and machine learning, mainly focusing on the robust and adaptive control of dynamical systems under uncertainty.

Previously, I earned my M.S. in Electrical Engineering from Caltech in 2023 and my B.S. in Electrical and Electronics Engineering, and B.S. in Physics from Bilkent University. During my undergraduate studies, I conducted research under the mentorship of Prof. Tolga Çukur. Additionally, I interned at Amazon, where I worked with Dr. Kevin Small, and at the National Magnetic Resonance Research Center.

Email: tkargin (at) caltech (dot) edu

Latest News

• (September 25, 2024) I gave a talk on our work Optimal Infinite-Horizon Mixed $H_2/H_\infty$ Control at the Allerton Conference 2024.
• (September 18, 2024) I am invited to present a poster at the Cornell ORIE Young Researchers Workshop 2024.
• (September 18, 2024) Invited talk at the UCSD Safe Autonomous System (SAS) Lab.
• (September 5, 2024) Invited talk at the Caltech Rigorous Systems Research Group (RSRG).
• (August 8, 2024) Invited talk at Bilkent University.
• (July 26, 2024) A new preprint on Distributionally Robust Kalman Filtering over Finite and Infinite-Horizon is available on arXiv.
• (July 25, 2024) I presented a poster on our paper Infinite-Horizon Distributionally Robust Regret-Optimal Control at ICML 2024.
• (July 25, 2024) I presented a poster on our paper Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis at ICML 2024.
• (July 24, 2024) Our paper The Distributionally Robust Infinite-Horizon LQR has been accepted for presentation at CDC 2024.
• (July 16, 2024) I presented a poster on our paper Wasserstein Distributionally Robust Regret-Optimal Control at L4DC 2024.
• (June 13, 2024) Invited talk at EE LSC Seminar Series at Caltech.
• (May 12, 2024) I am admitted to the Princeton Deep Learning Theory Summer School 2024.
• (May 1, 2024) Our two papers Infinite-Horizon Distributionally Robust Regret-Optimal Control and Learning the Uncertainty Sets of Linear Control Systems via Set Membership: A Non-asymptotic Analysis have been accepted for presentation at ICML 2024.
• (April 9, 2024) Our paper A Distributionally Robust Approach to Shannon Limits using the Wasserstein Distance has been accepted for presentation at ISIT 2024.
• (March 28, 2024) Our paper Wasserstein Distributionally Robust Regret-Optimal Control has been accepted for presentation at L4DC 2024.
• (August 7, 2023) Our paper Wasserstein Distributionally Robust Regret-Optimal Control under Partial Observability has been accepted for presentation at the Allerton Conference 2023.
• (June 26, 2023) I started my internship at Amazon as an Applied Scientist Intern under Dr. Kevin Small’s supervision.
• (June 6, 2023) I presented a poster on our paper Stochastic Mirror Descent in Mean-field Ensemble Models at ICASSP 2023.
• (June 2, 2023) I gave a talk on our paper Thompson Sampling for Partially Observable Linear-Quadratic Control at ACC 2023.
• (March 20, 2023) I passed my candidacy exam!
• (February 17, 2023) I presented a poster on our work Thompson Sampling Achieves $\tilde{\mathcal{O}}(\sqrt{T})$ Regret in Linear Quadratic Control at ITA 2023.
• (July 5, 2022) I gave a talk on our paper Thompson Sampling Achieves $\tilde{\mathcal{O}}(\sqrt{T})$ Regret in Linear Quadratic Control at COLT 2022.