Fernando De la Torre received his B.Sc. degree in Telecommunications, M.Sc. and Ph. D degrees in Electronic Engineering, respectively, in 1994, 1996 and 2002, from La Salle School of Engineering in Ramon Llull University, Barcelona, Spain. In 1997 and 2000 he became Assistant and Associate Professor in the Department of Communications and Signal Theory in Enginyeria La Salle. During his Ph. D, he was visiting researcher at Queen Mary and Westfield College (University of London), Institute of Advanced Computer Studies (University of Maryland), Xerox Palo Alto Research Center and Brown University. In 2002 he did a post-doc at Brown university (Providence, RI) and Gatsby Neuroscience Unit (London). In 2003 he became visiting research scientist in the Robotics Institute at Carnegie Mellon University. Since 2005 he is Research Scientist in the Robotics Institute at Carnegie Mellon University.

Dr. De la Torre's research interests include machine learning, signal processing and computer vision, with a focus on understanding human behavior from multimodal sensors (e.g. video, body sensors). His vision work is focused on face analysis (e.g. face tracking, recognition, expression/emotion analysis). In machine learning his interest is in developing efficient and robust methods for learning from high dimensional data. In particular, he has unified and extended many component analysis methods (e.g. kernel PCA, Linear Discriminant Analysis, spectral methods for clustering, Multidimensional Scaling). Dr. De la Torre has co-organized the first workshop on component analysis methods for modeling, classification and clustering problems in computer vision in conjunction with CVPR’07 and the workshop on human sensing from video in conjunction with CVPR’06. He has also given several tutorials at international conferences on the use and extensions of component analysis methods.

Interested in visiting the lab to work on machine learning and/or face image analysis? Send me your cv, indicate your availability and whether you have funding.