Assistant Professor

Department of Computer Science

University of Iowa

Room: #257, Macbride Hall

My Curriculum Vitae (October 2023)

About me

I am an Assistant Professor in Computer Science at the University of Iowa. Previously, I was a TRIPODS Postdoctoral Research Fellow at the University of Illinois at Urbana Champaign, working with Prof. R. Srikant as my Postdoc advisor. I received my B.Sc. from the Sharif University of Technology, Iran, in Mathematics as well as Electrical Engineering. I hold an M.Sc. in Electrical Engineering and a M.Sc. in Mathematics from the University of Michigan. I received my Ph.D. in Electrical Engineering in Winter 2020, for which I was awarded the Rackham Predoctoral Fellowship for an outstanding dissertation. I was fortunate to have  Prof. Mingyan Liu and Prof. Vijay Subramanian as my Ph.D. advisors.

My research so far spans two areas: (1) reinforcement learning and MDPs, and (2) computationally efficient algorithms for learning and economics in societal systems modeled as random graphs. (1) I study data-driven algorithms modeling the underlying environment as an MDP.  My main focus is to develop robust algorithms against distributional shifts and model uncertainties. (2) I study the impact of structural properties of real-world networks on interactions of individuals with fixed behavior, modeling the networks as a family of parameterized random graphs. My main focus is to understand and predict the results of interactions when the underlying parameter, and hence the structural properties of the network, varies.

My research interests are Markov decision processes, reinforcement learning, and random graph models for economics, learning, and computation.

Recent News:

Prospective Students

I have two open Ph.D. positions for prospective students with a strong background in mathematics. If you are interested in applying, contact me via email. However, the final decisions are made by the graduate committee.

Publications and Working Papers

Reinforcement Learning and MDPs:

Economics, Computation, and Learning in Random Graphs:     

Invited Talks

Honors and Awards

Professional Experiences