Publications: GPT-4V Cannot Generate Radiology Report Yet (ML4H 2024, NAACL 2025), The Use of Generative Search Engines for Knowledge Work and Complex Tasks, Can Domain Experts Rely on AI Appropriately? A Case Study on AI-Assisted Prostate Cancer MRI Diagnosis (FAccT 2025), Machine Explanations and Human Understanding (FAccT 2023, TMLR 2023, Best Paper at HMCaT @ ICML 2022), Towards a Science of Human-AI Decision Making: A Survey of Empirical Studies (FAccT 2023), Learning Human-Compatible Representations for Case-Based Decision Support (ICLR 2023), UNITE: Uncertainty-based Health Risk Prediction Leveraging Multi-sourced Data (WWW 2021), Toward a Thousand Lights: Decentralized Deep Reinforcement Learning for Large-Scale Traffic Signal Control (AAAI 2020)
Research Experience
Microsoft Research, Redmond, WA, US - Research Intern, Summer 2023; Amazon, AWS, Santa Clara, CA, US - Applied Scientist Intern, Summer 2022; IQVIA, Analytics Center of Excellence, Boston, MA, US - Machine Learning Research Intern, Summer 2020
Education
PhD student, Department of Computer Science, University of Chicago, Advisor: Chenhao Tan
Background
Research Focus: Understanding and improving LLMs for specialized tasks such as radiology and knowledge-intensive tasks; Human-AI collaboration. Passionate about putting humans at the center of AI development, including how to understand the process of human-AI interaction and how we can better build/deploy AI tools that can actually be useful in real-world settings.