Georgia Institute of Technology
Bits and Brains: Ultra-low Power, Neuro-inspired Edge-AI for Autonomous Systems
As we march towards the age of “ubiquitous intelligence”, we note that AI and Machine learning are progressively moving from the Cloud to the Edge devices. The success of Edge-AI is pivoted on innovative circuits and hardware that can enable inference and limited learning, in hardware-constrained ultra-low-power (uW to mW) systems – an area of active research. In this talk, I will discuss the promises and outlook of Edge-AI and their applications in Autonomous Systems; and elaborate on some of our recent work on enabling such systems in sensor nodes and robotics. While some of these systems extend our understanding of statistical machine learning, a large class of circuits and systems are inspired by the information representation in the brain. I will talk about the design of such circuits and systems with an emphasis on the impact of mixed-signal circuits, near-memory and in-memory compute architectures, non-CMOS (RRAM-based) compute macros, as well as algorithm-hardware co-design to realize the most energy-efficient Edge-AI ASICs for the next generation of smart and autonomous systems.
Arijit Raychowdhury is the Motorola Foundation Professor in the School of Electrical and Computer Engineering at the Georgia Institute of Technology. From 2013 to July 2019, he was an Associate Professor and held the ON Semiconductor Junior Professorship with the department. His industry experience includes five years as a Staff Scientist with the Circuits Research Lab, Intel Corporation, and two years as an Analog Circuit Researcher with Texas Instruments Inc. Dr. Raychowdhury’s research interests include low-power digital and mixed-signal circuit design and exploring interactions of circuits with device technologies. Dr. Raychowdhury has authored over 200 articles in journals and refereed conferences and holds more than 26 U.S. and international patents. Dr. Raychowdhury and his group have also received numerous awards and fellowships. Dr. Raychowdhury was the recipient of the Qualcomm Faculty Award in 2020, the IEEE/ACM Innovator under 40 Award in 2018, the NSF CISE Research Initiation Initiative Award (CRII), in 2015, Intel Faculty Award in 2015, the Intel Labs Technical Contribution Award, in 2011, the Dimitris N. Chorafas Award for outstanding doctoral research, in 2007. His students have also won several prestigious fellowships and 13 best paper awards over the years. He is a Senior Member of IEEE and currently serves on the technical program committees of several IEEE Conferences.