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
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.