Akshay Khunte is a medical student at the NYU Grossman School of Medicine and is currently a Sarnoff Cardiovascular Research Fellow in the CarDS Lab.

Akshay began his research at Yale’s Magnetic Resonance Research Center, where he worked on computational methods for metabolic imaging and brain tumor characterization. He then worked to investigate disparities in healthcare access, examining how insurance status and other barriers influence access to urgent and emergent care. During his undergraduate studies at Yale, where he majored in Computer Science and was a coxswain on the Men’s Lightweight Rowing team, he joined the CarDS Lab and began applying his interests in computing and healthcare accessibility to cardiovascular medicine.

His research focuses on using artificial intelligence to expand access to cardiovascular diagnostics and enable earlier detection of complex disease. His work has included developing methods to identify structural heart disease from wearable and portable ECGs, adapting diagnostic models to noisy real-world recordings, and building vision-language models for images of 12-lead ECGs. Across these efforts, he is particularly interested in how inexpensive and widely available modalities can be used to enable more sophisticated cardiovascular diagnostics. His work has been published in Circulation, npj Digital Medicine, the European Heart Journal, JAMA Cardiology, and the Journal of the American Medical Informatics Association, among others.

After graduating from Yale, Akshay began medical school at the NYU Grossman School of Medicine. He is now spending a dedicated research year at Yale as a Sarnoff Fellow with broader interests in developing and translating AI-enabled tools for earlier cardiovascular disease detection, improved risk assessment, and more personalized cardiovascular care.

Outside of medicine, Akshay enjoys reading, photography, and traveling.