Zihan Ding (丁子寒)
PhD candidate in Computer Science, Stony Brook University.
Human-centered AI for clinical decision support.
I am a PhD candidate in the Department of Computer Science at Stony Brook University, advised by Professor Fusheng Wang. Before that, I was fortunate to work with Professors Shan Lin and Yukun Yuan during my M.S. in Computer Science at Stony Brook, and with Professor Yuanting Yan during my B.E. in Computer Science and Technology at Anhui University.
My research builds machine learning models for clinical risk prediction that clinicians can actually interrogate: multimodal architectures over structured EHR data and clinical notes, interpretable risk stratification, and decision support tools designed together with the patients and clinicians who will use them.
Research
Within a PCORI-funded project where patients and clinicians co-define prediction targets, features, and evaluation criteria, I build opioid use disorder risk models and the dashboard clinicians use to compare them across cohorts.
Fusing structured records with unstructured clinical notes at the hidden-state level, using locally deployed LLMs so protected health information stays on-premise and each prediction stays traceable to the documentation behind it.
Registry-scale analyses of vaccination uptake, geographic access, and climate-related health outcomes across Long Island and New York State.
Publications
Manuscripts under review
Journal articles
Conference papers
Education
Experience
Biomedical informatics group of Fusheng Wang
CSE351 Data Science Fundamentals · CSE527 Computer Vision · CSE581 Theory
Mentoring
Multi-horizon opioid use disorder risk prediction using the All of Us cohort
Sequential models for opioid use disorder prediction across heterogeneous EHR sources