René Vidal

RENÉ VIDAL is a professor of Biomedical Engineering and the inaugural director of the Mathematical Institute for Data Science (MINDS) at Johns Hopkins University. He holds secondary appointments in the Departments of Computer Science, Electrical and Computer Engineering, and Mechanical Engineering, and is a faculty member of the Center for Imaging Science (CIS), the Institute for Computational Medicine (ICM), and the Laboratory for Computational Sensing and Robotics (LCSR).

Vidal’s research focuses on the development of theory and algorithms for the analysis of complex high-dimensional datasets, such as images, videos, time-series, and biomedical data. He has pioneered the development of methods for dimensionality reduction and clustering, such as Generalized Principal Component Analysis and Sparse Subspace Clustering, and their applications to face recognition, object recognition, motion segmentation, and action recognition. He has also helped create new technologies for a variety of biomedical applications, including detection, classification, and tracking of blood cells in holographic images, classification of embryonic cardio-myocytes in optical images, and assessment of surgical skill in surgical videos. His current major research focus is on understanding the mathematical foundations of deep learning and its applications in computer vision and biomedical data science.

Vidal is a Fellow of the IEEE and of the IAPR, and he has received numerous awards for his work, including the 2012 IAPR J.K. Aggarwal Prize, the 2009 ONR Young Investigator Award, the 2009 Sloan Research Fellowship, the 2005 NFS CAREER Award, and best paper awards in computer vision (JVCI 2015, ICCV-3DRR 2013, PSIVT 2013, ECCV 2004), controls (CDC 2012, CDC 2011) and medical robotics (MICCAI 2012).