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Physics Colloquium: Single Flux Quantum Based Neuromorphic Computing
April 9 @ 4:00 pm
National Institute for Standards and Technology (NIST)
Abstract: Neuromorphic computing promises to dramatically improve the efficiency of certain computational tasks, such as perception and decision making. While software and specialized hardware implementations of neural networks have made tremendous progress, both implementations are still many orders of magnitude less energy efficient than the human brain. This talk will introduce the current state of neuromorphic computing and discuss the recent hardware advances that have bolstered the progress of machine learning. I will discuss how a new superconducting platform, based on dynamically reconfigurable magnetic Josephson junctions with spiking energies less than one attojoule, could lead to large-scale neuromorphic systems with better energy efficiency than the human brain.
Bio: Michael Schneider is a Physicist at the National Institute of Standards and Technology in Boulder Colorado. He received his B.S. in physics from the University of Michigan in 1998 and his Ph.D. in physics from the University of Wisconsin in 2003. He has 15 years of research experience in experimental magnetism and spintronics. He has 8 years of research experience in experimental superconductivity and has spent the last 4 years working at the intersection of these fields. His current research is focused on novel ferromagnetic – superconducting devices and their applications including developing spiking neural networks with hybrid Josephson junction devices.
Berthoud Hall 241