Dr. Andreas Coppi is an Associate Research Scientist at the Cardiovascular Data Science (CarDS) Lab in the section of Cardiovascular Medicine and at the Center for Outcomes and Evaluation (CORE) of the Yale School of Medicine and Yale New Haven Health System.

Andreas has undergraduate degrees in Mathematics and Physics from MIT, and a PhD in Mathematics from Yale. Prior to joining the Yale School of Medicine, he worked for years in both industry and academia, working on devices and algorithms implementing signal and image processing as well as data modeling using applied computational harmonic analysis. He participated in several technology startups and helped co-author and manage a significant patent portfolio. In parallel, he also worked on Department of Defense contracts for many years as a Research Scientist in the Yale Mathematics Department.

For most of the last decade, he has worked in healthcare on methods for collecting and representing disparate sources of EHR, imaging, and other medical data for the purposes of analysis with modern machine learning or artificial intelligence methods, with the ultimate goal of implementing solutions in real-time that can deliver critical information to the bedside. His interests include computational healthcare, electronic health record databases, applied harmonic analysis, signal and image processing, machine learning and artificial intelligence, system architecture, and high performance computing.