Ceyhun Eksin

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June 2025 — Hosted two teachers in the Netmas lab as part of Spark!’s Enrichment Experiences in Engineering (E3) Program!

June 2025 — New PhD alert: S. Das succesfully defended his PhD thesis entitled “Learning , Intervention and Estimation in Dynamic Games”!!

May 2025 — Attended Texas Colloquium on Distributed Learning where S. Das and K. Nakhleh presented their posters.

April 2025 — New paper: Robust Information Design under Uncertain Payoffs in Quadratic and Gaussian Games with A. Arcaklioglu.

March 2025 — New paper: The Lagrangian Method for Solving Constrained Markov Games with S. Das, L. Chamon, and S. Paternain.

March 2025 — New paper: Examination of Health Behavior Models Ability to Predict Masking Behavior during COVID with Arthur, Pandit, Ndeffo-Mbah, Fields, and Smallman.

February 2025 — New paper: A Distributed and Coupled Policy Gradient Algorithm for Networked Multi-Agent Reinforcement Learning with P. Dai, D. Wang, S. Aydin, W. Yu

February 2025 — New paper: Actor-critic based reinforcement learning for multi-stage process planning and end point control in abrasive finishing operations with A. Karthikeyan, L. D. Kashyap and S. Bukkapatnam

January 2025 — Gave a talk on “Multi-Agent Learning in Dynamic and Competitive Environments” at Istanbul Technical University (my Alma Mater)!

December 2024 — Gave a talk at CDC ’24 on Learning Nash in Constrained Markov Games with an alpha-Potential in Milan!

October 2024 — New paper: Almost Sure Convergence of Networked Policy Gradient over Time-Varying Networks in Markov Potential Games with S. Aydin!

August 2024 — New acceptance alert: S. Das‘ paper on Learning Nash in Constrained Markov Games with an alpha-Potential accepted to IEEE Letters on Control Systems!

May 2024 — A. Karthikeyan is a finalist in the Manufacturing and Design Best Student Paper competition in IISE Annual Meeting with our paper on RL Based End Point Control for Polishing Operations.

April 2024 — Organized the TAMIDS Workshop on Multi-Agent Learning in Dynamic Environments. K. Nakhleh and S. Das provided an overview of their recent results.