I am an assistant professor at the University of Illinois Urbana-Champaign, Department of Statistics. At UIUC, I am also an affiliate assistant professor at the Department of Industrial & Enterprise Systems Engineering and an affiliate at the Carl R. Woese Institute for Genomic Biology. Additionally, I am an affiliate faculty member of the NSF-Simons National Institute for Theory and Mathematics in Biology (NITMB).

Before joining UIUC, I was a term assistant professor at Columbia University, Department of Statistics. I completed my Ph.D. in Operations Research & Financial Engineering at Princeton University in 2022 where I was the recipient of the School of Engineering and Applied Sciences Award for Excellence in 2021. Before starting my Ph.D., I graduated from Boğaziçi University with a Bachelor of Science in Industrial Engineering and a minor in Economics. During Fall 2021, I was a visiting graduate student at the University of Chicago to participate in the Distributed Solutions to Complex Societal Problems program of the Institute for Mathematical and Statistical Innovation (IMSI).

Broadly, I am interested in the theory, extensions, applications, and solutions of mean field games and control, graphon games, and Stackelberg games. I am especially interested in Stackelberg Mean Field Games to understand how the incentives imposed by a regulator affect the behavior of a large number of agents. Some of the applications I have worked on include: modeling of epidemics with human behavioral response and the effects of mitigation policies, the effect of carbon taxes on carbon emission levels, opinion dynamics, and the effect of advertisement in duopoly markets. Furthermore, I develop numerical approaches that make use of Machine Learning and Monte Carlo Simulations to solve these problems. On the learning from data side, I study inverse learning problems to learn individual objectives and unknown model parameters from observed behavior or population-level outcomes.

You can find my SIAM News article on how to optimally choose a carbon tax level on this link and you can find the Machine Learning Methods for Large Population Games with Applications in Operations Research Tutorial website here. I serve as an associate editor of Dynamic Games and Applications. My research is partially supported by NSF DMS.

You can find my CV here.