Experience

I have been actively engaged in pioneering research focused on the confluence of artificial intelligence, economics, and computation. My primary contributions revolve around the design and implementation of cutting-edge algorithms tailored for resource allocation and matching markets. One significant aspect of my work involves conducting thorough complexity analyses of these algorithms. This endeavor aims to understand and evaluate the efficiency and computational intricacies of the developed algorithms, ensuring their practical applicability and performance in various problem settings.

I was involved in Big Data project of analyzing a large set of student characteristics, incorporating  information on household, demography, and school performance. During this project, I performed detailed data preprocessing and manipulation, addressing missing values and data imbalance. To derive impactful policy insights, I developed and implemented complex predictive and machine learning algorithms in Python and MATLAB, advocating for targeted rural and gender-based educational initiatives.

• Teaching Assistant for Intermediate Microeconomics, Economics of Matching, PhD-level Mathematics for Economics, Money and Banking, Introductory Macroeconomic Analysis and Policy. 

• Referee for academic journals and conferences (AAMAS, Games and Economic Behavior,  Mathematical Social Sciences, WINE).

• I hold review and problem solving sessions for graduate-level Economic Theory and Mathematics (Optimization) classes.