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Temitayo Adeyeye (IntlAssoc)

Temitayo Adeyeye is pursuing his Ph.D. in the Electrical and Computer Engineering Department at the University of Maryland under the supervision of Advait Madhavan. He is currently working in the Alternative Computing Group in the Nanoscale Device Characterization Division of the Physical Measurement Laboratory (PML). His research interests include developing efficient hardware for AI inference and training, exploring brain-inspired computing architectures, robotics, and VLSI.

Publications

Measurement-driven Langevin modeling of superparamagnetic tunnel junctions

Author(s)
Liam Pocher, Temitayo Adeyeye, Sidra Gibeault, Philippe Talatchian, Ursula Ebels, Daniel Lathrop, Jabez J. McClelland, Mark Stiles, Advait Madhavan, Matthew Daniels
Superparamagnetic tunnel junctions are important devices for a range of emerging technologies, but most existing compact models capture only their mean

Neural networks three ways: unlocking novel computing schemes using magnetic tunnel junction stochasticity

Author(s)
Matthew Daniels, William Borders, Nitin Prasad, Advait Madhavan, Sidra Gibeault, Temitayo Adeyeye, Liam Pocher, Lei Wan, Michael Tran, Jordan Katine, Daniel Lathrop, Brian Hoskins, Tiffany Santos, Patrick Braganca, Mark Stiles, Jabez J. McClelland
Due to their interesting physical properties, myriad operational regimes, small size, and industrial fabrication maturity, magnetic tunnel junctions are
Created August 24, 2022, Updated April 18, 2023