Duygu Kuzum
Associate Professor
Dept. of Electrical and Computer Engineering
UC San Diego
Title: Innovating Beyond Electrophysiology: Multimodal Neural Interfaces and Computational Co-Design
Abstract:The next leap in implantable neural interfaces requires technological advances in materials, devices, and computing paradigms. Multimodal approaches enabled by 2D materials can allow concurrent optical and electrical sensing to overcome spatiotemporal resolution limits of neural sensing. Integration of sensing, computation and memory on a single array can enable real-time processing of neural signals for compact, low-power and high-throughput brain machine interfaces. Here, I will present this vision, its challenges, and discuss recent advances in the areas of transparent graphene neural interfaces for multimodal recordings, neuromorphic approaches for on-chip neural processing and computational co-design at the system level for minimally invasive neural interfaces.
Bio: Duygu Kuzum received her Ph.D in Electrical Engineering from Stanford University in 2010. She is currently an Associate Professor in Electrical and Computer Engineering Department at University of California, San Diego. Her group applies innovations in nanoelectronics to develop new technologies, which will help to better understand circuit-level computation in the brain. Her research also focuses on development of nanoelectronic synaptic devices for energy-efficient neuro-inspired computing. She is the author or coauthor of over 50 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), NSF Career Award (2018), NIH NIBIB Trailblazer Award (2018), NIH New Innovator Award (2020), and Joan and Irwin Jacobs-Kavli Foundation Chancellor's Endowed Faculty Fellowship for Engineering the Brain and the Mind (2023).
