Mehrdad Moharrami

Mehrdad Moharrami is an Assistant Professor in the Department of Computer Science at the University of Iowa. He specializes in reinforcement learning, Markov decision processes, and random graph models for economics and computational systems.

• Education: BSc in Mathematics and Electrical Engineering from Sharif University of Technology; MSc in Electrical Engineering and Mathematics from University of Michigan; PhD in Electrical Engineering from University of Michigan (2020)

His research focuses on robust reinforcement learning algorithms under distributional shifts and network structure analysis using parameterized random graphs. Recent work explores societal systems modeling and risk-sensitive control frameworks.

Moharrami's publications demonstrate interdisciplinary expertise across computer science, mathematics, and network science, with notable contributions to:

• Risk-sensitive reinforcement learning (ICML 2025, Mathematics of Operations Research 2024)
• Random graph modeling (COLT 2025, Random Structures & Algorithms 2024)
• Network optimization (IEEE Transactions on Network Science 2024, IEEE Transactions on Information Theory 2023)

Scientific recognition includes:

• Rackham Predoctoral Fellowship (2019)
• NSF MPS Workshop participation (2022)
• Multiple conference best paper nominations
• Iranian National Olympiad medals (2007-2008)

As co-organizer of major workshops (SIGMETRICS 2022, Performance 2023), he actively contributes to academic community development while maintaining active referee roles for top journals like IEEE/ACM Transactions on Networking and Mathematics of Operations Research.