Aug 16th (Fri) @ 10:00 am: “Photonic Architectures for In-Memory Computing Using Nonvolatile Optical Materials,” Nathan Youngblood, Ass’t. Prof., ECE, Pitt

Abstract

Photonics information processing strategies offer the unique ability to perform analog computation with ultra-low latency and high efficiency. However, designing compact and reconfigurable photonic architectures which scale well is a challenge. The combination of bistable optical materials (such as phase-change materials like Ge₂Sb₂Te₅) and integrated photonics is a promising approach which enables nonvolatile optical memory on-chip with low drift, compact footprint, and high-speed readout. This talk will focus on developing robust and scalable photonic memories—together with wavelength division multiplexing and “in-memory” computing techniques—to enable high-speed matrix-vector operations for machine learning applications.

Bio

Dr. Nathan Youngblood joined the Department of Electrical and Computer Engineering at the University of Pittsburgh as an Assistant Professor in September 2019. As a postdoctoral researcher at the University of Oxford from 2017 to 2019, he developed phase-change optical systems and photonic architectures for non-von Neumann computing. In 2016, he received a PhD in Electrical Engineering from the University of Minnesota where his research focused on integrating 2D materials with silicon photonics for optoelectronic applications. Nathan is a recipient of the NSF CAREER and AFOSR Young Investigator awards and his work has been published in leading journals such as Nature, Nature Photonics, and Science Advances, and featured in popular news outlets such as The Times, London and the Daily Mail.

Hosted by: Prof. John Bowers

Submitted by: Paolo Pintus <ppintus@ece.ucsb.edu>