Ben Liu is a researcher at Stanford Medicine working at the intersection of artificial intelligence, computer vision, and clinical medicine. He completed his BS and MS in Computer Science at Stanford, where he conducted research with the Stanford Medical AI and Computer Vision Lab (MARVL).
His work applies modern vision and language models to high-stakes medical settings. He co-authored "A human mesh-centered approach to action recognition in the operating room" (Artificial Intelligence Surgery, 2024), developing methods to understand surgical activity directly from video, and has studied fairness in clinical AI—including work showing that large language models display skin tone biases when evaluating common dermatological conditions, and SkinGPT-4, a generalizable foundation for fairer, customizable skin disease classification (Journal of Investigative Dermatology, 2025).
More recently, his research has focused on agentic and multimodal systems for clinical decision-making, including "Modeling Cognitive and Implicit Biases in Multi-Agent Medical Systems for Clinical Diagnoses" (ICCV 2025) and "Natural Language Grounded Reinforcement Learning for Clinical Decision-Making in Virtual Patient Simulations" (2025). He has also contributed to self-supervised learning for remote sensing, including USat, a unified encoder for multi-sensor satellite imagery.
Begin Your Journey
The application takes 5 minutes and is reviewed on a rolling basis. We look for strong technical signal—projects, coursework, or competition results—and a genuine curiosity to do real research.
If admitted, you will join a structured pipeline with direct mentorship to take your work from ideation to top conference submission at venues like NeurIPS, ACL, and EMNLP.
