Sara Fish
I am a fourth-year PhD student at Harvard advised by Yannai
Gonczarowski. My research interests lie in EconCS and ML. I am
supported by a NSF Graduate Research Fellowship and a Kempner
Institute Graduate Fellowship. Previously, I completed my B.S.
in Mathematics at Caltech.
I am always happy to chat with new people. Feel free to email me at sfish@g.harvard.edu or schedule a meeting here.
Research
Google Scholar
EconEvals: Benchmarks and Litmus Tests for LLM Agents in Unknown Environments
Sara Fish, Julia Shephard, Minkai Li, Ran Shorrer, and Yannai Gonczarowski
Preprint available at arXiv:2503.18825. (Code)
Generative Social Choice: The Next Generation
with Niclas Boehmer and Ariel Procaccia
ICML 2025 Oral (Top 1%) (arXiv:2505.22939). (Code)
Algorithmic Collusion by Large Language Models
with Yannai Gonczarowski and Ran Shorrer
Preprint available at arXiv:2404.00806.
Coverage: Marginal
Revolution, Zvi Mowshowitz, The Capitol Forum, CPI
TechREG Chronicle
Stable Menus of Public Goods: A Matching Problem
with Yannai Gonczarowski and Sergiu Hart
EC 2025 (arXiv:2402.11370). (Code)
Generative Social Choice
with Paul Gölz, David Parkes, Ariel Procaccia, Gili Rusak, Itai Shapira, and Manuel Wüthrich
EC 2024 (arXiv:2309.01291). (Code v2) (Code v3)
(Project awarded $100,000 grant via OpenAI's Democratic Inputs to AI
program.)
Crowd Science
I enjoy making small contributions to large scientific endeavors. Listed below are "crowd science" papers I coauthored as a middle (i.e., minor) author.
Prosocial Ranking Challenge (blog post, paper forthcoming)
This is a forthcoming study examining how interventions on social media ranking algorithms impact affective polarization among users. Our team's ranking algorithm submission was selected to be tested (top 3 of 21).
Humanity's Last Exam (arXiv:2501.14249)
This is a LLM benchmark consisting of questions submitted by researchers. Three questions I submitted were included, including one prize-winning question (top 550).
Comparing Human-Only, AI-Assisted, and AI-Led Teams on Assessing Research Reproducibility in Quantitative Social Science (EconPapers URL)
This study evaluates the effectiveness of AI at assisting or conducting reproducibility checks of economics papers. I contributed to the data-gathering process.
Teaching
- (Harvard) CS 37 / ECON 1071 ("Incentives in the Wild"): Teaching Fellow, Spring '25
- (Harvard) CS 37 / ECON 1071 ("Incentives in the Wild"): Teaching Fellow, Fall '23
- (Caltech) Ma 0 ("Intro to Proofs"): Lead Teaching Assistant, Summer '21
- (Caltech) Ma 6a ("Discrete Mathematics"): Teaching Assistant, Fall '19
- (Caltech) Ma 108a ("Real Analysis"): Grader, Fall '19
Miscellaneous
Others' work
Previous volunteering and employment
Previous math research
A Construction for Difference Sets with Local Properties
with Ben Lund and Adam Sheffer
European Journal of Combinatorics, Vol. 79, June 2019, pg. 237-243. arXiv
Crescent configurations in Normed Spaces
with D. King, S. J. Miller, E. A. Palsson, and C. Wahlenmayer
Integers, Vol. 20, #A96. arXiv
Local Properties via Color Energy Graphs and Forbidden Configurations
with Cosmin Pohoata and Adam Sheffer
SIAM Journal on Discrete Mathematics, Vol. 34, Jan 2020, pg. 177-187. arXiv
