Brigham and Women's Hospital, United States
I am currently a PGY-3 resident and postdoctoral research fellow of I6 cardiothoracic surgery (cardiac track) at Brigham and Women’s Hospital/Harvard Medical School and my research interest has always been applying machine learning in cardiothoracic surgery. My academic training and research experience have provided me with an excellent background in multiple clinical and computer science disciplines including cardiovascular pathophysiology, various computer programming languages (MATLAB, SAS, R programming, etc.), image and signal processing algorithms, and machine learning models (Decision tree, neural networks, kernel-based methods, Bayesian learning, fuzzy reasoning, and mixed-effect Longitudinal models). As a medical student, I was able to conduct multiple research projects with Dr. Alireza Ghavidel in cardiac surgery which resulted in a patent and innovative technique to preoperatively measure optimal length of artificial chordae in mitral valve repair, new image processing algorithm for detecting micro-emboli in echocardiography images, and a new machine learning model (Fuzzy Decision Tree) to predict outcomes after coronary artery bypass graft surgery. As a postdoctoral fellow with Dr. Rakesh Suri at Mayo clinic and Dr. Marc Gillinov at Cleveland clinic, my research focused on heart valve disease and applying innovative mathematical models in outcome research. During this period, I gained expertise in various mitral valve repair techniques as well as complex mathematical analysis techniques. I was first author in multiple papers and book chapters published in Nature Cardiology Review, Journal of Thoracic and Cardiovascular Surgery, Journal of American Thoracic Surgery, Journal of American College of Cardiology, etc. During my medical school and postdoctoral fellowships, I received several academic awards as well.
Disclosure information not submitted.
Friday, October 25, 2024
5:30 PM – 5:45 PM EST