I’m a fifth year PhD student in Operations Research at Cornell University, where I am fortunate to be advised by Professor Peter Frazier. Prior to Cornell, I completed my undergraduate in Mathematics and Physics at Haverford College and earned my Master’s degree in Management Science & Engineering at Stanford University.
My research interests lie at the intersection of machine learning and operations research. My current research focuses on designing novel Bayesian optimization algorithms for drug discovery and materials design. More generally, I am interested in researching and utilizing data science, operations research and machine learning to engender substantial real-world impact.
In Summer 2022, I interned at Meta Core Data Science (CDS) in the Adaptive Experimentation team, mentored by Daniel Jiang. In Fall 2022, I continued my work at Meta as a student researcher.
In April 2020 - May 2022, I worked with a fabulous COVID mathematical modeling team to model the spread of COVID-19 since pandemic began. Leveraging techniques from stochastic modeling, simulation and optimization, our model directly guided Cornell’s president and provost on reopening and intervention decisions, and has influenced policies at many other US universities. Our work has appeared in news media such as ABC news, the Wall Street Journal, the Asahi Shimbun and more.
In my spare time I like hiking, cooking, and trying something new.
Contact me at firstname.lastname@example.org.
Download my resume (last updated January 2023).
Ph.D. in Operations Research, Expected 2024
M.S. in Management Science & Engineering, 2018
B.S.in Mathematics and Physics, 2016
All modeling reports are published online here.