Eric Tramel is a principal research scientist and leader with 13+ years of experience at the intersection of statistical physics, signal processing, and machine learning, now focused on privacy-aware and federated learning in production settings. He earned a PhD in Computer Engineering and built early foundational work in compressed sensing for high-dimensional imagery, co-inventing a patented light-field acquisition system during a Canon research internship. Across postdocs in France and roles at Owkin, Amazon, Unlearn.AI, Gretel and now NVIDIA, he has transitioned academic advances—message-passing algorithms, unsupervised neural interpretations, and probabilistic digital-twin generators—into applied teams and deployable systems. He has published and lectured widely (ICML, NIPS) and led Owkin’s Federated Learning Research Group, blending algorithmic research, engineering, and regulatory-sensitive medical data work. Notably, his career threads deep theoretical insight with hands-on productization of privacy-preserving ML for healthcare and consumer devices.
13 years of coding experience
10 years of employment as a software developer
PhD Computer Engineering, PhD Computer Engineering at Mississippi State University
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Eric Tramel - Principal Research Scientist at NVIDIA