René VidalProfessor

RESEARCH INTERESTS
Machine learning: mathematics of deep learning, subspace clustering, sparse and low-rank representation, manifold learning and clustering, matrix factorization, time series classification, GPCA, kernel GPCA, dynamic GPCA
Computer vision: 3D scene analysis, activity recognition, 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
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
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.