I am an assistant 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. Most of my work deals with the development of computational methods for (1) inferring models from images (image/video segmentation, motion segmentation), static data (subspace clustering) or dynamic data (identification of hybrid systems), and (2) using such models to accomplish a complex task (track fibers in the brain, recognize actions in videos, land a helicopter on a moving platform, pursue a team of evaders, follow a formation, etc.)

Biomedical image analysis: estimation and processing of high angular resolution diffusion imaging (HARDI), registration and segmentation of diffusion MRI, segmentation and fiber tracking of cardiac MRI, interactive medical image segmentation, heart motion analysis

Computer vision: camera sensor networks, activity recognition, dynamic texture segmentation and recognition, 3D motion segmentation, 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: 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.

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 the Fall of 2003 and joined The Johns Hopkins University in January 2004 as an Assistant Professor in the Department of Biomedical Engineering and the Center for Imaging Science. Dr. Vidal was co-editor (with Anders Heyden and Yi Ma) of the book ``Dynamical Vision" and has co-authored more than 100 articles in biomedical image analysis, computer vision, machine learning, hybrid systems, and robotics. Dr. Vidal is Associate Editor of the Journal of Mathematical Imaging and Vision, and was a program chair for WMVC 2009, PSIVT 2007 and area chair for CVPR 2005 and ICCV 2007. Dr. Vidal is recipient of 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) for his work on "A Unified Algebraic Approach to 2-D and 3-D Motion Segmentation" presented 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 member of the IEEE and the ACM.

Diego Rother: object segmentation, reconstruction and recognition using 3D shape priors

Ertan Cetingul (PhD BME): fiber tracking, heart motion analysis, diffusion weighted imaging

Rizwan Chaudhry (PhD CS): kernels on dynamical systems and activity recognition

Ehsan Elhamifar (PhD ECE): sparse representation theory, manifold clustering, robust consensus, observability and identification of hybrid systems

Alvina Goh (PhD BME): estimation, processing, segmentation and registration of diffusion weighted images, manifold clustering

Avinash Ravichandran (PhD ECE): registration, segmentation and recognition of dynamic textures

Dheeraj Singaraju (PhD ECE): discrete optimization, object recognition and segmentation, image matting and segmentation, 2D motion segmentation

Roberto Tron (PhD ECE): consensus on manifolds, camera sensor networks, motion segmentation

Mihaly Petreczky: (post-doc, now at CWI, Netherlands) realization theory for hybrid systems

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'.