Hybrid Machine Learning for Complex Systems: Algorithm and Architecture to Couple Model-Based and Data-Driven Learning

Mukhopadhyay, Saibal

Title:

Hybrid Machine Learning for Complex Systems: Algorithm and Architecture to Couple Model-Based and Data-Driven Learning

dc.contributor.author	Mukhopadhyay, Saibal
dc.contributor.corporatename	Georgia Institute of Technology. Center for Research into Novel Computing Hierarchies	en_US
dc.contributor.corporatename	Georgia Institute of Technology. School of Electrical and Computer Engineering	en_US
dc.date.accessioned	2018-12-07T20:51:01Z
dc.date.available	2018-12-07T20:51:01Z
dc.date.issued	2018-11-02
dc.description	Presented on November 2, 2018 at 2:30 p.m. in the Klaus Advanced Computing Building, Room 1116 East/West, Georgia Institute of Technology (Georgia Tech)	en_US
dc.description	Second Annual Center for Research into Novel Computing Hierarchies (CRNCH) Summit, November 2, 2018 at Georgia Tech.	en_US
dc.description	Saibal Mukhopadhyay (S'99-M'07-SM'll-F'l8) received the B.E. degree in electronics and telecommunication engineering from Jadavpur University, Kolkata, India, and the Ph.D. degree in electrical and computer engineering from Purdue University, West Lafayette, IN, in 2000 and 2006, respectively. He is currently a Joseph M. Pettit Professor with the School of Electrical and Computer Engineering, Georgia Institute of Technology, Atlanta. His research interests include design of energy-efficient, intelligent, and secure systems. His research explores a crosscutting approach to design spanning algorithm, architecture, circuits, and emerging technologies. Dr. Mukhopadhyay was a recipient of the Office of Naval Research Young Investigator Award in 2012, the National Science Foundation CAREER Award in 2011, the IBM Faculty Partnership Award in 2009 and 2010, the SRC Inventor Recognition Award in 2008, the SRC Technical Excellence Award in 2005, the IBM PhD Fellowship Award for years 2004 to 2005. He has received IEEE Transactions on VLSI Best Paper Award (2014), IEEE Transactions on Component, Packaging, and Manufacturing Technology Best Paper Award (2014), and multiple best paper awards in International Symposium on Low-power Electronics and Design (2014, 2015, and 2016). He has authored or co-authored over 200 papers in refereed journals and conferences, and holds five U.S. patents. Dr. Mukhopadhyay is a Fellow of IEEE.	en_US
dc.description	Runtime: 26:15 minutes	en_US
dc.description.abstract	An all-day summit featuring plenary talks on the future of computing and panel discussions.	en_US
dc.format.extent	26:15 minutes
dc.identifier.uri	http://hdl.handle.net/1853/60598
dc.language.iso	en_US	en_US
dc.publisher	Georgia Institute of Technology	en_US
dc.relation.ispartofseries	CRNCH Summit
dc.subject	Computer architecture	en_US
dc.subject	Computing	en_US
dc.subject	Energy efficient systems	en_US
dc.subject	Intelligent systems	en_US
dc.subject	Secure systems	en_US
dc.subject	Technologies	en_US
dc.title	Hybrid Machine Learning for Complex Systems: Algorithm and Architecture to Couple Model-Based and Data-Driven Learning	en_US
dc.type	Moving Image
dc.type.genre	Presentation
dspace.entity.type	Publication
local.contributor.author	Mukhopadhyay, Saibal
local.contributor.corporatename	Center for Research into Novel Computing Hierarchies (CRNCH)
local.relation.ispartofseries	CRNCH Summit
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