Monson H. Hayes
- Cátedras de Excelencia
- Cátedras de Excelencia 2014
- Monson H. Hayes
Monson H. Hayes
Monson H. Hayes
Chung-Ang UniversityGeorge Mason University, Fairfax VA US
Monson Hayes received his B.A. in Physics from the University of California at Berkeley in 1971, and his S.M. and Sc.D. degrees in electrical engineering and computer science from M.I.T. in 1981.
Dr. Hayes was a Professor of Electrical and Computer Engineering at the Georgia Institute of Technology from 1981 until 2011, and served as an Associate Chair in the School of ECE at Georgia Tech, and as Associate Director for Georgia Tech Savannah. Dr. Hayes is currently Professor Emeritus at Georgia Tech. From 2011 until 2014 he was a Distinguished Foreign Professor at Chung-Ang University, Seoul, Korea, in the Graduate School of Advanced Imaging Science, Multimedia, and Film. Currently, he is Professor and Chair of the Department of Electrical and Computer Engineering at George Mason University in Fairfax, Virginia.
Dr. Hayes has served the Signal Processing Society of the IEEE in numerous positions, including General Chairman of ICASSP-96, ICIP-2006, and ICASSP-2018. Dr. Hayes has published over 200 papers, is the author of two textbooks, and has received numerous awards and distinctions from professional societies as well as from Georgia Tech. His research interests are in the areas of digital signal processing, image and video processing, adaptive signal processing, machine learning and pattern recognition, and engineering education. Dr. Hayes is a Life Fellow of the IEEE.
Research stay at UC3M: DEPARTMENT OF SIGNAL THEORY AND COMMUNICATIONS
Project:
At UC3M some state-of-the-art research is being done on deep learning algorithms that may be applied to some very difficult image understanding problems. In particular, researchers at UC3M are focusing their attention along two very exciting and promising directions: Machine Ensembles and Deep Learning.
It has been verified that by combining different sources of diversity and extending diversity to consecutive aggregation steps increases the effectiveness and performance of machine ensemble designs. Therefore, this project will involve the application of these techniques to problems of practical importance and significance such as image understanding and scene description.
Stay period: JAN 15 - JUL 15