Tuesday, September 20, 2022, 9:00-10:00am PDT / 18:00-19:00 CET

INRC Member Tech Talk – Qinru Qiu (Syracuse University)

Open

Visualizing the temporal activity and outputs of a neuromorphic system.

Neuromorphic Computing for Energy Efficient Near Sensor Adaptive Machine Intelligence

Abstract: IoT and edge devices are on the frontier of interacting with the physical world for sensing, perception, and recognition. The limited battery capacity of these devices demands highly energy efficient information representation, computing and communication. The constantly changing environment and mission requirements call for the ability of online learning and adaptation. Inspired by the structure and behavior of biological neural systems, spiking neural network (SNN) models and neuromorphic computing hardware adopt many energy-efficient features of biological systems. They have been proven to be effective for mobile and edge applications. In this talk I will introduce our work on applying SNNs and neuromorphic computing in processing multivariate time sequences such as sensor readings. Using neurons modeled as a network of infinite impulse response filters, our SNN network can either work as a classifier to detect temporal patterns from the input sequences or as a generator to generate desired temporal sequence. The ability to discern temporal patterns allows us to adopt very sparse input representation, where information is encoded by the intervals between spike events. When coupled with event driven computing and communication, such temporal coding provides significant energy savings. Online learning and domain adaptation of the model will also be discussed in this talk.

Open

Bio: Dr. Qinru Qiu received her PhD in Electrical Engineering from University of Southern California in 2001. She is currently a professor and the director of the graduate program in the Department of Electrical Engineering and Computer Science at Syracuse University. Dr. Qiu has more than 20 years of research experience in machine intelligence and more than 15 years’ experience in neuromorphic computing. She is a recipient of NSF CAREER award in 2009, and IEEE Region 1 Technological Innovation award in 2020. She serves as an associate editor for IEEE Transactions on Neural Networks and Learning Systems (TNNLS), IEEE Circuit and Systems Magazine, IEEE Transactions on Cognitive and Developmental Systems, and Frontier on Neuroscience on Neuromorphic Engineering. She has also served as a technical program committee member of many conferences including DAC, ICCAD, ISLPED, DATE, etc. She is the director of the NSF I/UCRC (Industry University Collaborative Research Center) ASIC (Alternative Sustainable and Intelligent Computing) Center Syracuse Site.

How to join:

INRC Members can find the meeting link on INRC Fall Forum Schedule. If you are interested to become a member, join the INRC.