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 research focuses on development of nanoelectronic synaptic devices for energy-efficient neuro-inspired computing. Her group applies innovations in nanoelectronics to develop new technologies, which will help to better understand circuit-level computation in the brain. 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, 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).
Abstract
The next leap in implantable neural interfaces requires technological advances in materials, devices, and computing paradigms. Holistic approaches integrating optical and electrical sensing modalities can overcome spatiotemporal resolution limits of neural sensing as well as open up new avenues for non-invasive neural recording. 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, we present this vision, its challenges, and discuss recent advances in the areas of transparent 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.
