PhD Candidate · Computational and Data Sciences
Building responsible AI for public health, social science, and human decision-making.
I am a PhD candidate in Computational and Data Sciences at Washington University in St. Louis and a McDonnell International Scholar. My research brings together agentic AI, qualitative inquiry, public health, and human-centered decision-making.
Advised by Dr. Ruopeng An and Dr. Jiaxin Huang.
Academic impact
Google Scholar · Daily sync
Publication count includes published, in-press, and accepted journal articles and CS conference papers; excludes book chapters.
Research
Three connected directions in qualitative research, decision-making, and public health.
I develop and evaluate LLM-assisted workflows for thematic analysis and grounded theory coding. My work examines how retrieval, multi-agent collaboration, and transparent audit trails can support rigorous qualitative inquiry.
I study how LLM agents simulate economic preferences, survey responses, and health-related decisions. I compare their behavior with empirical evidence to understand when these simulations are informative—and where they fall short.
I evaluate AI applications in mental health, vaccine safety, and health communication, focusing on reliability, interpretability, and accountability. My goal is to support tools that remain responsive to the people and settings they serve.
AI systems should complement established empirical and qualitative methods rather than obscure them.
Tools should remain interpretable, culturally sensitive, and accountable to the people affected by them.
Research should support better health communication, policy reasoning, and real-world decisions.
I welcome interdisciplinary collaborations spanning AI, public health, and social work.
I enjoy Chinese cooking and dessert-making, making music on the piano, violin, and harmonica, and playing badminton.