Sadegh Talebi

Sadegh Talebi is a Tenure Track Assistant Professor in the Machine Learning Section at the Department of Computer Science, University of Copenhagen. His research focuses on theoretical aspects of reinforcement learning, Markov decision processes, online learning, stochastic multi-armed bandit problems, and resource allocation in networks.

• Education
  • BSc in Electrical Engineering (minor: Electronics) from Iran University of Science and Technology (IUST) (2004)
  • MSc in Electrical Engineering (minor: Communication Systems) from Sharif University of Technology (2006)
  • PhD in Electrical Engineering from the Department of Automatic Control at KTH Royal Institute of Technology (supervised by Alexandre Proutiere and Mikael Johansson)
• Research
  • Specializes in theoretical foundations of reinforcement learning and online learning
  • Key contributions in stochastic optimization, MDPs, and bandit algorithms
  • Collaborates on applications in resource allocation and quantum computing

Publications include high-impact work on offline RL, differentially private exploration, and scalable MDP solutions in journals like Neural Processing Letters and conferences such as NeurIPS and UAI.