Sunny Chung, MD

Sunny Chung is a gastroenterologist and clinical informatics researcher at Yale School of Medicine whose work focuses on improving complex, high-impact decision-making in gastroenterology. He completed his medical training at Yale, internal medicine residency at Duke University Hospital, and fellowship in gastroenterology at Yale, where he also earned a Master of Health Science in Clinical Informatics.

Dr. Chung’s research integrates generative artificial intelligence, machine learning, and implementation science to modernize the way clinicians use real-world data and clinical evidence, particularly in scenarios where uncertainty is high and decisions carry significant consequences. He tries to address the patient–evidence applicability mapping problem: the challenge of aligning individual patient states with the most relevant medical evidence under conditions of incomplete observability. He operates across two layers: the representational (recovering high-fidelity patient and evidence states from unstructured data) and the structural (quantifying the 'structural-semantic gap' where citation and influence dynamics decouple clinical applicability from institutional visibility). By integrating clinical phenotyping, evidence synthesis, and metascience, he aims to define the fundamental limits of evidence alignment and build the validated infrastructure needed for point-of-care precision medicine.

He is the recipient of national recognition as an American Gastroenterological Association (AGA) Innovation Fellow and an American Society for Gastrointestinal Endoscopy (ASGE) AI Scholar. His work has been published in leading journals including Gastroenterology and npj Digital Medicine, and he serves as an Editorial Fellow for Clinical Gastroenterology and Hepatology.