About me

Hello there! I’m a 5th year Ph.D. candidate in Operations Research at Stanford University MS&E, where I’m very fortunate to be advised by Itai Ashlagi. My research interests are in design and analysis of marketplaces, such as online market platforms and kidney allocation waitlists. Broadly speaking, I use tools from mechanism design, optimization, and machine learning.

In Summer 2021, I interned at Facebook as a Data Scientist within Ads & Business Product (ABP), where I conducted causal inference studies. In Summer 2020, I interned at Lyft as a Research Scientist within Rideshare, where I developed machine learning models to predict driver ETAs. In academic year 2020-2021, I was the student organizer of the RAIN (Research on Algorithms and Incentives in Networks) seminar.

Research

  • Counterbalancing Learning and Strategic Incentives in Allocation Markets (working paper)
  • Observational Learning in Waitlist Mechanisms (working paper)

Education

  • Ph.D., Operations Research, Stanford University MS&E. 2017 - 2022 (Expected)
  • M.S., Operations Research, Stanford University MS&E. 2019.
  • B.S., Operations Research, Columbia University IEOR. 2013 - 2017

Teaching

  • MS&E 220: Probabilistic Analysis (Summer 2019, Fall 2019)
  • MS&E 230: Incentives and Algorithms (Spring 2020)
  • MS&E 260: Intro to Operations Management (Fall 2020)
  • IEOR 4150: Intro to Probability and Statistics (Fall 2016)