Hi! I’m Connie. I’m a Master's student in Management Sciences & Engineering (Computational Social Sciences Track) at Stanford, where I have the privilege to be mentored by Professor Omer Reingold and Dr. Lee Cohen.
Currently, my research centers around creating more fair and robust predictors motivated by empirical observations of societal dynamics. I hope to achieve this by intersecting topics from machine learning and algorithmic game theory!
During my undergraduate studies, I extended work in strategic classification to design algorithmic interventions that enhanced both accuracy and fairness in resume-screening systems, accounting for the potential use of LLMs by job applicants.
Previously, I've also built AI-Agent evaluation tools with
Runloop AI, and OCR pipelines for the
U.S. Census Bureau.
Research Interests
Economics and Computation, Algorithmic Fairness, Machine Learning Theory.
Publications
Two Tickets are Better than One: Fair and Accurate Hiring Under Strategic LLM Manipulations.
Cohen, L., Hsieh J.,
Hong, C., Shen, J.
ICML 2025,
Swap Regret and Strategic Learning Workshop @ EC 2025
Misc. Writing
How Do Disparities Emerge? Unpacking Confidence and Accuracy Gaps by Gender and Socioeconomic Status.
Hong, C.
Data Science B.S. Capstone Project (2025).
Spatiotemporal Modeling of Chicago Traffic Accidents with Convolutional and LSTM Networks.
Gu, Z.,
Hong, C, Torrecilla, I.
Final Project for CS 229: Machine Learning (2024).
Teaching
I'm a current CA for
MATH51: Linear Algebra and Multivariable Calculus as a part of Stanford's ACE Program, which allows me to foster my passion for making mathematics accessible to all!
Outside of academics, I also love exploring graphic design! Here are some of my previous works as a designer for Stanford's Division of Literatures, Cultures, & Languages: