ECE Seminar series

Speaker Name: 
Duygu Kuzum
Speaker Organization: 
UCSD Neuroelectronics
Start Time: 
Monday, April 1, 2019 - 10:40am
Location: 
E2-192

Abstract: Neuro-inspired architectures and reconfigurable-adaptive systems are emerging research fields aiming to go beyond capabilities of digital logic and eventually to reach brain-like learning efficiency. In this talk, I will present novel electronic devices for neuro-inspired computing, performing weight updates to implement learning in the hardware. I will discuss several aspects of neuro-inspired computation including energy efficiency, robustness and parallelism. Then I will briefly discuss how neuro-inspired algorithms can be implemented using synaptic devices. In the second part of my talk, I will introduce a new flexible transparent neural probe made of graphene for simultaneous electrophysiology and neuroimaging. Understanding dynamics of neural circuits requires probing them with high spatial and temporal resolution, simultaneously. Graphene-based neurotechologies enable seamless integration of optical and electrical modalities to probe neural circuits with high spatio-temporal resolution.

Biography: Duygu Kuzum received her Ph.D in Electrical Engineering from Stanford University. She is currently an Assistant Professor in Electrical and Computer Engineering Department at University of California, San Diego. Her research focuses on applying innovations in nanoelectronics to develop new technologies, which will help to better understand circuit-level computation in the brain. She develops nanoelectronic synaptic devices for energy-efficient neuro-inspired computing. She is the author or coauthor of over 40 journal and conference papers. She was a recipient of a number of awards, including Texas Instruments Fellowship and Intel Foundation Fellowship, Penn Neuroscience Pilot Innovative Research Award (2014), Innovators under 35 (TR35) by MIT Technology Review (2014), ONR Young Investigator Award (2016), IEEE Nanotechnology Council Young Investigator Award (2017), and NSF Career Award (2018).