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Computer Vision & AI
Visión por computadora e Inteligencia Artificial
Carlos Avilés-Cruz
Professor - Researcher, UAM-AZC Multimedia Lab.
Contact Information:
Multimedia Lab, G301-17
Electronics Department, Av. San Pablo 180, Col Reynosa, 02200.
Ciudad de Mexico, Mexico City
Email: caviles@azc.uam.mx
Phone: (+52) 55 53 18 90 30
Miembro del Sistema Nacional de Investigadores / National Research System member
Miembro de la IEEE / IEEE member
Miembro de la Academia Mexicana de Computación / Member of the Mexican Academy of Computing
Orcid bar code http://orcid.org/0000-0002-2323-9335
Short Biography
Doctor Carlos Avilés Cruz was born in Mexico City (March 13, 1966). He is graduated in Electronics Engineering (1989) from the Universidad Autónoma Metropolitana-Mexico City, He received the master degree in signal and image processing from the National Institute Polytechnic of Grenoble- FRANCE (1993). He received the Doctor degree in signal and image processing from the National Institute Polytechnic of Grenoble- FRANCE (1997). Currently, he is a full-time professor at the Universidad Autónoma Metropolitana- Mexico City. His research interests are artificial intelligence, computer vision, digital signal and image processing and High Order Statistics. Doctor Avilés is author and co-author of about 100 national and international articles and also co-author of two books.
After a French Ph.D. from the Institute National Polytechnic of Grenoble, France. He joined the Autonomous Metropolitan University in the Electronics Department in 1997. He is the founder of the multimedia lab. and collaborator with Institute National Polytechnic (IPN), Mexican National Autonomous University (UNAM), Institute National Polytechnic of Grenoble and ENSTA Bretagne-France.
His research is cross-disciplinary, spanning pattern recognition, computer vision, biomedical engineering and cognitive neuroscience. His main contributions are over human and machine recognition, scene understanding, as well as in imagery movement by EEG signal. His research integrates knowledge and tools from image processing, signal processing, high order statistics, computer vision, computer science as well as human action recognition (by mobile devices).
Research Overview
My cross-disciplinary research in Biomedical Engineering, Computer Science and Computer Vision, bridges from theory to experiments to applications, solving problems through a novel proposal.
Computer Vision
Augmented Reality
Human Action Recognition