Chen Lab
Jonathan H. Chen, MD, PhD.
Assistant Professor of Medicine, Computational Medicine
Dr. Chen is a physician-scientist with professional software development experience as an entrepreneur and graduate training in computer science. He practices Internal Medicine for the reward of caring for patients and to inspire research, mining clinical data sources to inform recommendations for medical decision-making.
Dr. Chen is an expert in Electronic Health Records, Data-Mining, Crowd-sourcing, Recommender Systems, Collaborative Filtering, Observational Research, Medical Decision Making, Machine Learning, Secondary Analysis, Clinical Decision Support. Dr. Chen joined Stanford BMIR in 2017 as an Assistant Professor.
Bryan Bunning
Bryan is a PhD student in Biomedical Informatics Research interesting in bridging informatics solutions to advancing the access to and execution of modern clinical trial.
Ethan Goh
Dr. Ethan Goh is a research fellow with a background in informatics, digital health transformation, and strategic innovation. His research at Stanford focuses on leading multi-site, grant-funded evaluation of Large Language Model applications within healthcare.
Francois Grolleau
Post-Doctoral Fellow François is an Anesthesiology and Critical Care Medicine physician. His research work centers on developing and evaluating computational systems that use advanced methods from statistics and machine learning to assist medical decision-making.
Fateme Nateghi Haredasht
Fateme Nateghi is a postdoctoral scholar at the Stanford Center for Biomedical Informatics Research (BMIR). She develops AI tools to improve healthcare delivery, focusing on machine learning models that combine structured EHR data and clinical notes. Her research centers on post-training and evaluation of large language models (LLMs) to ensure accurate, reliable, and clinically useful outputs. She is also interested in embedding-based retrieval and retrieval-augmented generation (RAG) to connect AI innovation with clinical practice. Fateme holds a PhD in Biomedical Sciences from KU Leuven, where she specialized in time-to-event modeling for healthcare applications.
Ruoqi Li
Ruoqi Liu is a post-doctoral researcher. She earned her Ph.D. in Computer Science and Engineering from The Ohio State University. Her research has centered on the intersection of artificial intelligence and causal inference, with an emphasis on improving causal effect estimation and enabling reliable decision-making in healthcare and biomedicine. At Stanford, she is interested in developing agentic AI systems powered by large language models, with applications in scientific discovery and healthcare.
Iván López
Iván is a medical student dedicated to advancing the field of machine learning by exploring and implementing methods for extraction of unstructured data from electronic health records.
Minh Nguyen
Minh is a Ph.D. student in the Biomedical Informatics program. She is interested in clinical informatics, causal inference, and measurement/label bias