I am a second-year PhD student in computer science at the University of Pennsylvania. I am fortunate to be advised by Michael Kearns, Aaron Roth, and Duncan Watts. I am broadly interested in the intersection of Machine Learning Theory, Algorithmic Game Theory, and Reinforcement Learning/Control (especially their practical and social applications). Prior to this, I graduated from Stanford University with a B.A.S. in Mathematics and Economics (Honors). During my time there, I was lucky to work with and be advised by Matthew Jackson, Itai Ashlagi, and Alain Schläpfer. I also spent a year working in the Dynamic Stochastic General Equilibrium (DSGE) Team at the New York Federal Reserve.

Publications

(all in alphabetical ordering)

• Boss LLM: Adaptation via No-Regret Learning. Joint work with Y. Feng, A. Khare, and N. Nguyen. ICLR: SSI-FM 2025, Manuscript.
• Intersectional Fairness in Reinforcement Learning with Large State and Constraint Spaces. Joint work with E. Eaton, M. Hussing, M. Kearns, A. Roth, and J. Sorrell. JHU DSAI Symposium on Human-AI Alignment 2025, Manuscript.
• Oracle-Efficient Reinforcement Learning for Max Value Ensembles. Joint work with M. Hussing, M. Kearns, A. Roth, and J. Sorrell. ICML: ARLET, WIML, NeurIPS: Main 2024.
• Estimating HANK for central banks. Joint work with S. Acharya, W. Chen, M. Del Negro, K. Dogra, A. Gleich, S. Goyal, E. Maitlin, D. Lee, and R. Sarfati. FRB of New York Staff Report.

Research/Experience

• Advised by Matthew Jackson for my Honors Thesis, I studied the role of homophily in the malleability of social networks using techniques drawn from Mean-Field Game Theory here
• Worked on online estimation of Heterogeneous Agent New Keynesian Models (HANK) using Sequential Monte Carlo at the NY Federal Reserve. I also briefly worked on speeding up Hamiltonian Monte Carlo (HMC) to estimate medium-scale DSGE models.
• Developed an algorithm with Itai Ashlagi that matches students in the San Francisco area with schools based upon a generalized version of the Probabilistic Serial Dictatorship mechanism with distributional constraints
• Collaborating with Alain Schläpfer on Reinforcement Learning and Imitation Learning for Optimal Stopping Problems here
• Civic Digital Fellow in Research & Statistics through Coding it Forward where I worked on Imputation of Revenue for the County Business Patterns dataset for the U.S. Census Bureau

Mentorship/Involvement

• Women in Machine Learning Volunteer
• Computer and Information Science Student Seminar Co-Founder
• Computer and Information Science Theory Seminar Volunteer
• CS UPenn PhD Mentorship Program Volunteer
• Stanford Women in Math Mentoring Member
• Stanford Undergraduate Mathematics Organization Member

Teaching

• TA for Algorithmic Game Theory (Spring 2025)
• Mathematics and Economics Tutor through the Stanford Center for Teaching and Learning

Awards/Honors

• Phi Beta Kappa
• Graduated with Distinction (Top 15% of Undergraduate Body)
• Coleman Sellers Award

Hobbies

Outside of research, I love to play chess, juggle, and watch films!