Rakin is currently a final year MD candidate at Dartmouth, who was recently inducted into Alpha Omega Alpha. He graduated with a PhD in Biophysics at Harvard Medical School, having been inducted into Sigma Xi, where he was co-advised by Bruce Rosen [1] and Jayashree Kalpathy-Cramer [2] in the QTIM lab at MIT and the MGH/HST Martinos Center for Biomedical Imaging. His dissertation was titled 'Generating Clinically Translatable AI Models for Cancer Diagnostics' at the intersection of computer science, biophysics, engineering, and medicine; his work resulted in multiple publications, presentations at national and international conferences, as well as several honors and awards [3], including the Mind, Brain, Behavior (MBB) Award.

Rakin studied Biomedical Engineering, Applied Math and Economics during his undergrad as a member of the Class of 2018 at Dartmouth on a full-ride scholarship, graduating with High Honors, Phi Beta Kappa, Tau Beta Pi and Magna Cum Laude, and took part in an exchange at the University of Oxford in the UK. His MD admittance, which he started straight through, was via the highly competitive Biomedical Engineering (BME) Early Assurance Program (EAP), which waived the MCAT and featured a single streamlined application with multiple interview rounds.

Rakin's clinical and research interests lie at the intersection of AI/deep learning, medicine, biomedical imaging and genomics. Rakin is broadly interested in addressing issues pertaining to AI deployment and model robustness (e.g., repeatability, generalizability), with a long-term goal of integrating deep learning (DL) into clinical workflows to augment the clinician, thereby potentially replacing costly, risky, and invasive tests.