معرفی
Lovedeep Singh Dhingra is a Postdoctoral Associate at Yale School of Medicine, working in the Cardiovascular Data Science (CarDS) Lab within the Department of Internal Medicine. He holds a Master of Health Science (MHS) degree in Clinical Informatics & Data Science from Yale (2025) and completed his MBBS at All India Institute of Medical Sciences (AIIMS), New Delhi (2020).
His research focuses on applying machine learning, computer vision, and natural language processing to cardiovascular diagnostics, electronic health record analysis, and public health applications. Dr. Dhingra's work bridges clinical medicine with advanced computational techniques to improve cardiovascular care through AI-driven insights from ECG images and other diagnostic data.
His research trends show a strong emphasis on developing and validating AI algorithms for structural heart disease detection, heart failure risk prediction, and diabetes management. His publications demonstrate expertise in handling real-world clinical data across multinational settings, with particular attention to algorithm robustness and clinical applicability.
Dr. Dhingra actively contributes to significant research initiatives including the DIRECT-DM digital registry for type 2 diabetes and the LEGEND-T2DM multinational effort assessing cardiovascular outcomes of diabetes therapies.
He collaborates extensively with leading researchers including Rohan Khera, Harlan Krumholz, and Arya Aminorroaya, with whom he has numerous co-publications in top cardiovascular journals. His work has been published in prestigious journals including European Heart Journal, Journal of the American College of Cardiology, Circulation, JAMA Cardiology, and Nature Cardiovascular Research.
At Yale, Dr. Dhingra is part of the vibrant research ecosystem centered around the Cardiovascular Data Science Lab, which focuses on innovation through data-driven discoveries to improve cardiovascular outcomes and advance precision medicine approaches in cardiology.
