معرفی
René Vidal is the Rachleff & Penn Integrates Knowledge (PIK) University Professor at the University of Pennsylvania, with appointments in the Departments of Electrical and Systems Engineering, Radiology, Computer and Information Science, and Statistics and Data Science. He also serves as Director of the Center for Innovation in Data Engineering and Science (IDEAS) and the NSF-Simons Collaboration on the Mathematical Foundations of Deep Learning (THEORINET). A dual faculty member at Johns Hopkins University in Biomedical Engineering, Computer Science, and other departments, Vidal is an Amazon Scholar and Affiliated Chief Scientist at NORCE.
- PhD, Electrical Engineering and Computer Sciences, University of California, Berkeley (2003)
- M.S., Electrical Engineering, University of California, Berkeley (2000)
- B.S. (valedictorian), Electrical Engineering, Pontificia Universidad Catolica de Chile (1997)
His research spans the mathematical foundations of deep learning, focusing on non-convex optimization, learning dynamics, and overparametrization. Key contributions include Sparse Subspace Clustering, Kernel GPCA, and Low-Rank Matrix Factorization, with applications in autism diagnosis, robotic surgery, and cardiac imaging. Recent work explores continual learning, adversarial robustness, and trustworthy AI in biomedical contexts.
His 15 most recent publications highlight advances in medical imaging, language models, and robust computer vision, spanning topics from chest X-ray analysis to motor imitation tasks in autism. Articles like Geometric Analysis of Nonlinear Manifold Clustering underscore his theoretical contributions, while works on KDA: Knowledge-Distilled Attacker and Conformal Information Pursuit address practical AI safety and interpretability.
Scientific accolades include:
- 2022 ACM Fellow
- 2021 IEEE McCluskey Technical Achievement Award
- 2017 Jean D’Alembert Fellowship
- 2012 J.K. Aggarwal Prize
- 2009 Sloan Research Fellow
- 2005 NSF CAREER Award
His lab mentors 11 current PhD students across Johns Hopkins and University of Pennsylvania, with alumni contributing to institutions like Meta, Amazon, and GE Research. Vidal’s interdisciplinary work bridges mathematics, engineering, and healthcare, supported by grants from the DoD, NSF, and ONR.
