Building Brain-inspired Computing Small, Cool, and Robust: Novel Paradigms for Analog Neuromorphic Circuit Design

Speaker:  Dr. Yang (Cindy) Yi

Host: MICS

Date: September 15 (Friday), 2017
Time: 2:30 PM - 3:30 PM
Location: Whittemore 654 (6th Floor Conference Room)

Abstract:

Brain-inspired computing has attracted significant attention recently due to its potential superior performance. The recently emerged research on “neuromorphic computing”, which is inspired by the working mechanism of human brain, holds great promise for many emerging engineering and scientific applications. By using very-large-scale integration (VLSI) circuits to mimic neuro-biological architectures present in the nervous system, neuromorphic computing will power the next wave of artificial intelligence.

Our presentation starts with a background introduction of neuromorphic computing, followed by the summary of our research work on high performance and energy efficient analog neuromorphic computing integrated circuit (IC) design. Spike time dependent encoding efficiently maps a signal’s amplitude information into a spike time sequence that offers perfect recovery for band limited stimuli. The nonlinear delay feedback reservoir node represents a class of dynamic processors that meet the requirements of high dimensionality and finite memory. Three dimensional (3D) integration with neuromorphic IC provides high system speed, high density, low power consumption, and small footprint. At the end, we will show the application of the proposed design and methodology in anomaly detection and channel symbol detection.

Bio:

Yang (Cindy) Yi is an assistant professor in the Bradley Department of Electrical and Computer Engineering (ECE) at Virginia Tech (VT). Prior to joining VT, she has been working on various research topics in the area of Integrated Circuits and Systems (ICS) at Texas A&M University (TAMU), University of Kansas (KU), Freescale, IBM, Intel, and Texas Instruments (TI). She obtained her Ph.D. in Electrical and Computer Engineering at Texas A&M University, the M.S. and B.S. in Electrical Engineering at Shanghai Jiao Tong University. Her research interests lie in general areas in Very Large Scale Integrated (VLSI) Circuits and Systems, Neuromorphic Computing, Computer Aided Design (CAD), Emerging Nano-electronic Device, and Internet of Things (IoT).

Yang (Cindy) Yi has more than 70 publications in international journals and conference proceedings. 5 of her paper have been selected as Best Paper Award at IEEE GLOBECOM in 2016, Best Paper Award Finalist at ACM GLSVLSI in 2017, IEEE ISQED in 2017, IEEE VLSI-DAT in 2011, and IEEE EPEP in 2006. Yang (Cindy) Yi has been invited to serve as Technical Program Committee (TPC) track chair in IEEE ISQED and MWSCAS, an editorial board member for several international journals including Elsevier NCN, IJCNE, EJAET, and JSAM. She received the United States Air Force (USAF) Summer Faculty Fellowship, Miller Professional Development Award for Distinguished Research in 2016, KU Miller Scholar, NSF EPSCoR First Award, USAF Summer Faculty Fellowship, KU New Faculty General Research Award in 2015, Air Force Research Lab (AFRL) Visiting Faculty Research Fellowship, and University Academic Program Faculty Scholar in 2014. Yang (Cindy) Yi’s research has been funded by NSF, Department of Defense (DoD), NSF EPSCoR, AFRL, AFSOR, and several industrial companies (Intel, Samsung, NVidia, and TI).