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Brian Hoskins (Fed)

Physicist

Brian Hoskins is a research physicist in the Alternative Computing Group in the Nanoscale Device Characterization Division of the Physical Measurement Laboratory (PML). He received both a B.S. and an M.S. in Materials Science and Engineering from Carnegie Mellon University and a Ph.D. in Materials from the University of California, Santa Barbara. For his doctoral research, he developed and characterized resistive switching devices for use in neuromorphic networks. Brian is working on CMOS integration of resistive switches for the development and characterization of intermediate scale neuromorphic networks.

Projects

Selected Publications

  • Optimized stateful material implication logic for three-dimensional data manipulation, G. C. Adam, B. D. Hoskins, M. Prezioso, D.B. Strukov, Nano Research 9, 3914 (2016). [doi]
  • Training and operation of an integrated neuromorphic network based on metal-oxide memristors, M. Prezioso*, F. Merrikh-Bayat*, B.D. Hoskins *, G.C. Adam, K.K. Likharev, and D.B. Strukov, Nature 521, 7550 (2015). [doi] *Equal Contributor
  • Resistive switching and its suppression in Pt/Nb:SrTiO3 junctions, E. Mikheev, B.D Hoskins, D. B. Strukov, and S. Stemmer, Nature Communications 5, 3990 (2014). [doi]

Publications

Implementation of a Binary Neural Network on a Passive Array of Magnetic Tunnel Junctions

Author(s)
Jonathan Goodwill, Nitin Prasad, Brian Hoskins, Matthew Daniels, Advait Madhavan, Lei Wan, Tiffany Santos, Michael Tran, Jordan Katine, Patrick Braganca, Mark Stiles, Jabez J. McClelland
The increasing scale of neural networks and their growing application space have produced a demand for more energy and memory efficient artificial-intelligence

A System for Validating Resistive Neural Network Prototypes

Author(s)
Brian Hoskins, Mitchell Fream, Matthew Daniels, Jonathan Goodwill, Advait Madhavan, Jabez J. McClelland, Osama Yousuf, Gina C. Adam, Wen Ma, Muqing Liu, Rasmus Madsen, Martin Lueker-Boden
Building prototypes of heterogeneous hardware systems based on emerging electronic, magnetic, and photonic devices is an increasingly important area of research
Created May 7, 2019, Updated September 7, 2022