Chao Yan, PhD, is a research instructor in the Department of Biomedical Informatics at Vanderbilt University Medical Center (appointed in February 2025), following the completion of his postdoctoral fellowship in the same department. He earned his PhD in computer science from Vanderbilt University in 2022. Dr. Yan’s research focuses on developing computational methods, particularly AI/ML algorithms, to unlock the full potential of biomedical data while promoting its ethical use to improve health care delivery. His work spans several key areas: (i) creating generative AI algorithms for synthetic health data generation to broaden health data access and maximize their analytical value; (ii) designing trustworthy AI/ML models for disease diagnosis and intervention; (iii) leveraging large language models and graph technologies to accelerate biomedical research and clinical applications; and (iv) applying network science to reveal complex structures in health care systems and their associations with patient outcomes.
He is the recipient of the NIH NLM K99/R00 Pathway to Independence Award and the TN-CFAR Development Core Award, both awarded in 2024. His work has been recognized with numerous honors, including selection for one of the best articles in clinical research informatics published in 2020 (featured in the 2021 International Medical Informatics Association Yearbook) and a Distinguished Paper Award at the 2019 AMIA Annual Symposium.
Dr. Yan is an active contributor to the medical informatics community. He was an elected member of the JAMIA Student Editorial Board and currently serves on the JAMIA Editorial Board for the 2025-2027 term. He has also been invited to serve as an Editor for Special Issues and Collections in leading journals such as BMC Medical Informatics and Decision Making. Additionally, he was a member of the Scientific Program Committee for the 2024 AMIA Annual Symposium and serves as the lead organizer and moderator of the NIH AIM-AHEAD AI Optimization Discussion Forum series.
ORCiD: - https://orcid.org/0000-0002-6991-2687
Scopus Author ID: 57189348887
https://scholar.google.com/citations?hl=en&user=UCJrWSMAAAAJ
Dr. Mohammed Al-Garadi is a Research Assistant Professor in the Department of Biomedical Informatics at Vanderbilt University Medical Center. He previously worked as a Postdoctoral Researcher at Emory University, focusing on natural language processing (NLP), machine learning (ML), deep learning and large language models (LLMs) for healthcare applications. His research focuses on extracting insights from unstructured healthcare data, particularly unstructured notes, using NLP and machine learning techniques. By developing modules and pipelines, he has created systems to efficiently process diverse healthcare data streams. He worked on NIH and CDC grants involving the application of NLP and machine learning to analyze large-scale clinical narratives and public health data.
To date, Dr. Al-Garadi has authored and co-authored over 50 papers in high-impact scientific journals. Currently, Dr. Al-Garadi is exploring the potential of NLP, ML, and LLMs on unstructured EHR clinical notes for various healthcare applications. These include extracting, predicting, and detecting causes of death, postoperative infections, COPD exacerbations, kidney disease, peripheral artery disease, and tele-dermatology conditions and outcomes. He is working on projects supported by the NIH, Department of Veterans Affairs, and FDA.