About
Hi, I'm Yuen Chen
I am a CS PhD candidate at the University of Illinois Urbana-Champaign, advised by Prof. Hari Sundaram and Prof. Han Zhao.
My research connects causal machine learning with trustworthy AI. I study foundation models for causal discovery, including large language models and tabular foundation models. I also evaluate causal reasoning in language models, use causal interventions to understand bias and reduce harmful outputs, and develop methods for learning representations that generalize across domains.
At Capital One AI Foundation, I explored in-context learning and tabular foundation model pretraining for causal discovery in summer 2026. In summer 2025, I studied how learning jointly from user activity and social networks improves predictions, leading to our LoG 2026 paper.
I previously interned at the Max Planck Institute for Intelligent Systems in Tübingen, Germany, working with Prof. Bernhard Schölkopf and Zhijing Jin. I hold a B.A. in Applied Mathematics & Statistics from UC Berkeley (Dec 2022).
Selected Publications