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.