Catherine Chen is interested in studying settings in which machine learning models fail. In particular, she investigates solutions for problems, such as anomaly detection, distribution shifts, and uncertainty quantification. She obtained her undergraduate degree in Data Science, a joint major between Computer Science and Statistics, from Columbia University in 2022. She is now a second year Computational and Mathematical Engineering PhD candidate at Stanford University. Her current research involves risk control of Large Language Models (LLMs).