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Praveen Raghavan    
   

 

Bio

PRAVEEN RAGHAVAN, IMEC
DISTINGUISHED MEMBER OF TECHNICAL STAFF

Dr. Praveen Raghavan is a distinguished member of technical staff leading the group on various research fronts in the area of design enablement for advanced technology.  He is in charge of imec’s activity on system technology co-optimization to drive technology development from a system and design perspectives. One of the key projects he is leading is technology development for machine learning/neuromorphic computation. He has published over 300 conference and journal papers and holds more than 40 patents.

In his past, he has a vast span of projects he has been involved in from driving being the lead architect of IMEC’s multi-gigabit software-defined radio baseband chip set, decoders for radios. He also leads the project on driving Power-Performance-Area (PPA) and Design-Technology Co-optimization (DTCO) for imec logic scaling for 7nm, 5nm and beyond. His research interests include DTCO, PPAC, Device modelling, design methodologies, reliability, variability and low power design.

Dr. Praveen Raghavan obtained his PhD from KU Leuven in 2009, his Masters in Electrical Engineering from Arizona State University, USA and his Bachelors in Electrical Engineering from REC Trichy, India. In 2007, he was also a visiting researcher at Berkeley Wireless Research Center (BWRC), University of Berkeley, California. 

 

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Presentation abstract

IS THE TIME RIPE FOR A DEDICATED MACHINE LEARNING "TECHNOLOGY"?

Machine Learning/Artificial Intelligence is under a new felt revival in the field of software enthusiasts and computer architects designers. At the same time technologists are at a cross roads where memory scaling and logic scaling is getting to be extremely challenging from cost as well as from physics aspects. DRAM scaling roadmaps are looking at non-capacitor based technologies. Logic roadmaps are looking at the world of new compute paradigms and ‘beyond CMOS’ devices. Today the AI world is dominated by big data and big servers and not yet in the hands of common man. Given the market potential of AI, we will touch on various technology enablers that can push this market over the edge from being in the cloud to being in every digital product that surrounds us. Can technologists find a place in this space in this market?

 

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