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Elisa Vianello



Published on 7 October 2020


©CEA

Elisa Vianello

Edge AI Program Manager, CEA-Leti

​Schedule Time

  • 5:15 p.m: Artificial Intelligence: Hardware as a game changer

ABSTRACT

Resistive random access memory (RRAM) technologies, often referred to as memristors, hold fantastic promise for implementing novel in-memory computing systems for massively parallel, low-power and low-latency computation.
This talk will first present the role of RRAM to enable the hardware implementation of Spiking Neural Networks (SNN). The resistive memories technologies can play a crucial role in the hardware implementation of the three main SNN building blocks: learning and memory, communication and computation. Second, we will present a new path towards realizing intelligent systems, compatible with fundamental resistive memory properties, particularly cycle-to-cycle variability, to bring learning to the edge.

BIO

  • Elisa is a senior scientist at CEA-Leti. She joined the institute in 2011 after spending one year on the research staff at Fondazione Bruno Kessler, Trento. 
  • Her current research interests concern the development of new technologies for bio-inspired neuromorphic computing, with special focus on resistive switching memory devices (RRAM) and phase change memory (PCM). She has authored or co-authored 4 book chapters and more than 100 technical papers.
  • She is coordinator of the "MeM-Scales" (2020-2022) European project (H2020) focused on the codevelopment of a novel class of algorithms, devices and circuits that reproduce multi-timescale processing of biological neural systems. 
  • She also is associate editor of the APL special issue on Emerging Materials in Neuromorphic Computing (February 2020) and of the incoming IEEE Transactions on Circuits and Systems –II (2020-2021).
  • She received the PhD in Electrical Engineering from the Università degli Studi di Udine (Italy) and the Grenoble Institute of Technology (INPG, France) in 2010.