René Vidal, PhD

Associate Professor of Biomedical Engineering,
Computer Science, Mechanical Engineering, and
Electrical and Computer Engineering

302B Clark Hall
3400 N Charles St.
Baltimore MD 21218, USA

Phone: 410-516-7306
Fax: 410-516-4557
E-mail: rvidal at jhu dot edu
About me
I am an associate professor in the Department of Biomedical Engineering at The Johns Hopkins University. I direct the Vision Dynamics and Learning Lab, which is part of the Center for Imaging Science (CIS). I am also a faculty member in the Institute for Computational Medicine (ICM) and the Laboratory for Computational Sensing and Robotics (LCSR). My research areas are biomedical image analysis, computer vision, machine learning, dynamical systems theory and robotics. I am particularly interested in the development of mathematical methods for the interpretation of high-dimensional data, such as images, videos, and biomedical data. In particular, I have developed methods from algebraic geometry, sparse and low-rank representation theory for clustering and classification of high-dimensional data, and methods from dynamical systems theory for modeling and comparison of time series data. Applications include motion segmentation, dynamic texture classification, object and activity recognition in images and videos, surgical skill and gesture recognition in kinematic and video, segmentation and registration of brain images, and classification of cardiac myocytes.
Research Interests
  • Biomedical image analysis: gesture and skill recognition in robotic surgery, analysis of high angular resolution diffusion images (HARDI), classification of stem cell derived cardiac myocites, interactive medical image segmentation segmentation and fiber tracking in cardiac MRI, interactive medical image segmentation, heart motion analysis
  • Computer vision: activity recognition in video and motion capture, semantic segmentation of images and videos, dynamic texture segmentation and recognition, 3D motion segmentation, camera sensor networks, non-rigid shape and motion analysis, structure from motion and multiple view geometry, omnidirectional vision
  • Machine learning: manifold clustering, kernels on dynamical systems, GPCA, kernel GPCA, dynamic GPCA
  • Dynamical systems: observability, identification, realization, metrics and topology for hybrid systems
  • Robotics: gesture and skill recognition in robotic surgery, formation control of teams of non-holonomic robots, coordination and control of multiple autonomous vehicles for pursuit-evasion games, multiple view motion estimation and control for landing an unmanned aerial vehicle
  • Signal processing: consensus on manifolds, distributed optimization, compressive sensing.
  • Brief Bio
    Professor Vidal received his B.S. degree in Electrical Engineering (highest honors) from the Pontificia Universidad Catolica de Chile in 1997 and his M.S. and Ph.D. degrees in Electrical Engineering and Computer Sciences from the University of California at Berkeley in 2000 and 2003, respectively. He was a research fellow at the National ICT Australia in 2003 and has been a faculty member in the Department of Biomedical Engineering and the Center for Imaging Science of The Johns Hopkins University since 2004. He has held several visiting faculty positions at Stanford, INRIA/ENS Paris, the Catholic University of Chile, Universite Henri Poincare, and the Australian National University. Dr. Vidal was co-editor (with Anders Heyden and Yi Ma) of the book ``Dynamical Vision" and has co-authored more than 150 articles in biomedical image analysis, computer vision, machine learning, hybrid systems, robotics and signal processing. Dr. Vidal is Associate Editor of the IEEE Transactions on Pattern Analysis and Machine Intelligence, the SIAM Journal on Imaging Sciences and the Journal of Mathematical Imaging and Vision. He was or will be program chair for ICCV 2015, CVPR 2014, WMVC 2009, and PSIVT 2007. He was area chair for CVPR 2013, ICCV 2011, ICCV 2007 and CVPR 2005. Dr. Vidal is recipient of numerous awards for his work, including the 2012 J.K. Aggarwal Prize for ``outstanding contributions to generalized principal component analysis (GPCA) and subspace clustering in computer vision and pattern recognition", the 2012 Best Paper Award in Medical Robotics and Computer Assisted Interventions (with Benjamin Bejar and Luca Zappella), the 2011 Best Paper Award Finalist at the Conference on Decision and Control (with Roberto Tron and Bijan Afsari), the 2009 ONR Young Investigator Award, the 2009 Sloan Research Fellowship, the 2005 NFS CAREER Award and the 2004 Best Paper Award Honorable Mention (with Prof. Yi Ma) at the European Conference on Computer Vision. He also received the 2004 Sakrison Memorial Prize for "completing an exceptionally documented piece of research", the 2003 Eli Jury award for "outstanding achievement in the area of Systems, Communications, Control, or Signal Processing", the 2002 Student Continuation Award from NASA Ames, the 1998 Marcos Orrego Puelma Award from the Institute of Engineers of Chile, and the 1997 Award of the School of Engineering of the Pontificia Universidad Catolica de Chile to the best graduating student of the school. He is a fellow of the IEEE and a member of the ACM.

    Complete CV.

    Current PostDocs
  • Bijan Afsari: averaging on Riemannian manifolds, metrics on dynamical systems, activity recognition
  • Luca Zappella: language or surgery, motion segmentation
  • Erdem Yoruk: modeling and inference for visual recognition
  • Current Graduate Students
  • Evan Schwab (PhD ECE): analysis of diffusion MRI data
  • Benjamin Bejar (MSc BME): language of surgery
  • Lingling Tao (PhD ECE): language of surgery
  • Siddharth Mahendran (PhD ECE): joint segmentation and categorization of objects in images and videos
  • Giann Gorospe (PhD BME): classification of cardiac myocites
  • Former PhD Students and PostDocs
  • Aastha Jain (post-doc 2012, now at Linkedin): joint segmentation and categorization of objects in images and videos
  • Roberto Tron (PhD ECE, 2012, now at Upenn): consensus on manifolds, localization of camera sensor networks, motion segmentation
  • Rizwan Chaudhry (PhD CS 2012, now at Microsoft): kernels on dynamical systems and activity recognition
  • Ehsan Elhamifar (PhD ECE, 2012, now at UC Berkeley): sparse subspace clustering, block-sparse classification, manifold clustering, robust consensus, observability and identification of hybrid systems
  • Ertan Cetingul (PhD BME 2011, now at Siemens Corporate Research): fiber tracking, heart motion analysis, processing, segmentation and registration of diffusion weighted images
  • Diego Rother (post-doc 2009-2011, now at Google): object segmentation, reconstruction and recognition using 3D shape priors
  • Avinash Ravichandran (PhD ECE 2010, now at UCLA): registration, segmentation and recognition of dynamic textures
  • Dheeraj Singaraju (PhD ECE 2010, then at UC Berkeley, now at Google): discrete optimization, object recognition and segmentation, image matting and segmentation, 2D motion segmentation
  • Alvina Goh (PhD BME 2010, now at National University of Singapore): estimation and processing of diffusion weighted images, manifold clustering
  • Mihaly Petreczky: (post-doc 2007-2008, then at CWI Netherlands, now at Ecole des Mines de Douai) realization theory for hybrid systems
  • Prospective Students
    If you are interested in joining my lab, please apply directly to the department your are most interested in: Applied Mathematics and Statistics, Biomedical Engineering, Computer Science, Electrical and Computer Engineering, or Mechanical Engineering. Please make sure to mention my name in your statement of purpose. Once you have applied, please send me an e-mail with a subject such as 'PhD Application to BME 2009'.