| Start Date: | 4/18/2014 | Start Time: | 4:00 PM |
| End Date: | 4/18/2014 | End Time: | 5:30 PM |
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Event Description
Duygu Kuzum, PhD, postdoctoral researcher in the department of bioengineering at the University of Pennsylvania, will discuss how the efficiency of today’s information processors has been dominated by transistor scaling based on Moore’s law and how, in the nano-era, device scaling started to face significant barriers in achieving historical performance gains. Besides the scaling limits, the conventional computing paradigm based on binary logic and Von Neumann architecture becomes increasingly inefficient as the complexity of computation increases. Brain-inspired architectures and reconfigurable-adaptive systems are emerging research fields aiming to go beyond capabilities of digital logic and eventually to reach brain-level efficiency. In this first part of her talk, Dr. Kuzum will present a novel electronic device for brain-inspired computing, mimicking functionalities of biological synapses in the brain. She will discuss several aspects of brain computation including energy efficiency, robustness and parallelism and compare with state-of-the-art super computers. Dr. Kuzum will explain how we can use synaptic devices in brain-inspired architectures to demonstrate learning and robustness in hardware. She will then discuss how synaptic devices can help understanding brain computation. In the second part of her talk, Dr. Kuzum will introduce a new flexible transparent neural probe made of graphene. She will discuss electrochemical characteristics and noise performance of transparent probes in in vivo recordings. She will then explain how the transparent probes enable simultaneous calcium imaging and electrophysiology in hippocampal slices to study circuit dynamics with high spatio-temporal resolution. For more info, please visit: www.biomed.drexel.edu. |
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Location:
Papadakis Integrated Sciences Building (PISB), Room 120, located at the corner of 33rd and Chestnut Streets. |
Audience:
AlumniInternational StudentsCurrent StudentsFacultyProspective StudentsPublicStaffGraduate Students |
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