I am a tenure-track Assistant Professor for Mathematics of Machine Learning in the Department of Mathematics at RWTH Aachen University.

My research interests lie in theoretical machine learning, optimization and probability theory, with a focus on:

• theoretical and algorithmic foundations of reinforcement learning,
• deep learning theory,
• online learning and bandits.

Prior to joining RWTH, I was an NSF Postdoctoral Research Fellow at the University of Illinois at Urbana-Champaign, affiliated with IDS2 and ODI Group at ETH Zurich.

Selected Papers

• Sample Complexity and Overparameterization Bounds for TD Learning with Neural Network Approximation [paper]
  Semih Cayci, Siddhartha Satpathi, Niao He, R. Srikant
  IEEE Transactions on Automatic Control Special Issue on Learning and Control, Vol. 68, May 2023.
  
• Convergence of Entropy-Regularized Natural Policy Gradient Methods with Linear Function Approximation [paper]
  Semih Cayci, Niao He, R. Srikant
  ICML Workshop on Reinforcement Learning Theory 2021
• A Lyapunov-Based Methodology for Constrained Optimization with Bandit Feedback
  Semih Cayci, Yilin Zheng, Atilla Eryilmaz
  AAAI 2022
  [paper]
• Group-Fair Online Allocation in Continuous Time
  Semih Cayci, Swati Gupta, Atilla Eryilmaz
  NeurIPS 2020
  [paper]
• Budget-Constrained Bandits over General Cost and Reward Distributions
  Semih Cayci, Atilla Eryilmaz, R. Srikant
  AISTATS 2020
  [paper]

Teaching

• MATH 11.70010 - Mathematical Foundations of Reinforcement Learning (Winter 2022/23)
  

Miscellaneous

• I received my PhD from the Ohio State under the supervision of Prof. Atilla Eryilmaz.