Reconfigurable Electronic Materials Inspired by Nonlinear Neuron Dynamics (REMIND)



Stanley Williams

Lead Institution

Texas A&M Engineering Experiment Station




to establish foundational scientific knowledge underpinning the function of massively reconfigurable computing architectures that approach fundamental limits of energy efficiency and speed, enabling real-time learning and embedded intelligence emulative of specific neuronal and synaptic functions of the human brain.

Partner Institutions

  • Texas A&M Exp Station
  • NREL
  • LBNL
  • SNL-NM

Quick Facts

Single Slide Overview
Technical Summary

BES Staff Contact

Aaron Holder