Learning Algorithms and Signal Processing for Brain-Inspired Computing [From the Guest Editors]

TY - JOUR

T1 - Learning Algorithms and Signal Processing for Brain-Inspired Computing [From the Guest Editors]

AU - Simeone, Osvaldo

AU - Rajendran, Bipin

AU - Gruning, Andre

AU - Eleftheriou, Evangelos S.

AU - Davies, Mike

AU - Deneve, Sophie

AU - Huang, Guang Bin

N1 - Funding Information: mathematics and biol- ogy; an M.S. degree in cognitive science; and a Ph.D. degree from the University of Ro - chester. She is a direc tor of research and group leader in the Department of Cognitive Science, Ecole Normale Supérieure (ENS), Paris. Her research interests focus on how biological neural circuits learn and solve probabilistic problems, as well as probabilistic approaches to human perception and psychiatry. Her recent results include networks learning to compute as efficiently and robustly as possible with spikes, entirely derived from an objective function combining errors in estimation (both in reproducing trained example and generalizing to new ones) and cost in number of spikes. She was awarded a Dorothy Hudgkin Fellowship from Royal Society London in 2004, a Marie Curie Team of Excellence fellowship in 2006, a MacDonnell Foundation Award in 2012, and a Brain and Human Cognition grant and a European Council Consolidator grant (from 2012 to 2017). Funding Information: ([email protected]) re- ceived his B.Tech. degree in instrumenta- tion from the Indian Institute of Technology Kharagpur in 2000 and his M.S. and Ph.D. degrees in electrical engineering from Stanford University, California, in 2003 and 2006, respectively. He is an associate professor of electrical and computer engineering at the New Jersey Institute of Technology. He was a master inventor and research staff member at the IBM T.J. Watson Research Center, New York, from 2006 to 2012 and a faculty member in the Electrical Engineering Department, the Indian Institute of Technology Bombay, from 2012 to 2015. His research focuses on building scalable architectures and systems for neuro-morphic computing using nanoscale devices. He has authored more than 75 papers in peer-reviewed journals and conferences and received 59 U.S. patents, four of which were awarded IBM’s high-value patent award. His research was supported by the U.S. National Science Foundation, Semiconductor Research Corporation, and companies such as Intel and IBM. He is a Senior Member of the IEEE. Funding Information: (osvaldo.simeone@kcl .ac.uk) received his M.Sc. degree (with hon- ors) and Ph.D. degree in information engi neering from the Politecnico di Milano, Italy, in 2001 and 2005, respectively. He is a professor of information engineering with the Centre for Telecommunications Research, Department of Engineering, King’s College London. From 2006 to 2017, he was a faculty member at the New Jersey Institute of Technology. He is a corecipient of the 2019 IEEE Communication Society Best Tutorial Paper Award, the 2018 IEEE Signal Processing Best Paper Award, the 2017 Best Paper by the Journal of Communication and Networks, the 2015 IEEE Communication Society Best Tutorial Paper Award, and the IEEE International Workshop on Signal Processing Advances in Wireless Communications 2007 and IEEE Conference on Wireless Rural and Emergency Communications 2007 Best Paper Awards. He was awarded a Consolidator Grant by the European Research Council in 2016. He is a Fellow of the IEEE and of the Institution of Engineering and Technology.

PY - 2019/11

Y1 - 2019/11

UR - http://www.scopus.com/inward/record.url?scp=85074459728&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85074459728&partnerID=8YFLogxK

U2 - 10.1109/MSP.2019.2935557

DO - 10.1109/MSP.2019.2935557

M3 - Editorial

AN - SCOPUS:85074459728

SN - 1053-5888

VL - 36

SP - 12

EP - 15

JO - IEEE Signal Processing Magazine

JF - IEEE Signal Processing Magazine

IS - 6

M1 - 8887558

ER -