A biographical sketch

Prof. J.S. Sánchez, born in Reus (Tarragona, Spain), is a Full Professor at the Department of Programming Languages and Information Systems of Jaume I University (Castellón, Spain) and he is a member of the Computer Vision group. He received a B.Sc. in Computer Science from Technical University of Valencia in 1990 and a Ph.D. in Computer Science Engineering from Jaume I University in 1998. He was the winner of the 1997 Best Predoctoral Work Award of the Spanish Association for Artificial Intelligence. He is a member of IEEE Signal Processing Society, IEEE Neural Networks Society, IEEE Information Theory Society, IAPR, AERFAI (Spanish Association of Pattern Recognition and Image Analysis), ECCAI, and AEPIA (Spanish Association for Artificial Intelligence).
Prof. Sánchez is author or co-author of more than 100 scientific publications and co-editor of two books. He is an Associate Editor of the Pattern Analysis and Applications journal. He has served as guest editor for the special issue on "Advances in Pattern Recognition and Image Analysis" of the International Journal of Pattern Recognition and Artificial Intelligence, for the special issue on "Pattern Recognition and Image Analysis in Cybernetic Applications" in Cybernetics and Systems, and for the special issue on "Complexity Reduction in Efficient Prototype-based Classification" for the international journal Pattern Recognition.
He was a member of the organizing committee of the 8th Spanish Conference on Computational Geometry and co-chair of the 9th Spanish Symposium on Pattern Recognition and Image Analysis. Prof. Sánchez has served as reviewer for the international journals IEEE Trans. on Pattern Analysis and Machine Intelligence, Pattern Recognition Letters, Information Sciences, Information Fusion, Pattern Analysis and Applications, Pattern Recognition, Neurocomputing, IEEE Trans. on Neural Networks, IEEE Trans. on Knowledge and Data Engineering, Image and Vision Computing, and IEEE Robotics & Automation Magazine, as well as of a number of international conferences. His current research interests lie in the areas of pattern recognition and machine learning, including classification, information reduction (feature and prototype selection), ensembles of classifiers, semi-supervised learning, data complexity analysis, and classification of streaming data, as well as the application of pattern recognition techniques to robotics, industrial quality control, and gait analysis and recognition.