I am a PhD candidate in Applied Mathematics at the University of Maryland, where I am advised by Professor MohammadTaghi Hajiaghayi and supported by the National Science Foundation's Graduate Research Fellowship (NSF GRFP). My research explores the delicate balance between fairness and efficiency within combinatorial optimization, online algorithms, and machine learning. I develop algorithms that integrate fairness constraints into traditional problem frameworks, addressing both theoretical and practical challenges.

I also serve on the inaugural AAAI Student Committee and write for Scientific American through the AAAS Mass Media Fellowship.

I'm currently on the post-doc / job market. See my CV here.

Recent News:

• [December '24] Joining the Algorithms & Optimization Team at Google Research as an intern in January.

• [December '24] Invited talk at the 2024 Junior Theorists Workshop, hosted by Northwestern University and the Toyota Technical Institute at Chicago.

• [October '24] Invited research visit to the Max Planck Institute for Informatics in Saarbrücken, Germany.

• [September '24] Our paper "Fairness and Efficiency in Online Class Matching" has been accepted to NeurIPS 2024.