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Mark D. Stiles

Mark Stiles is a Project Leader and NIST Fellow in the Alternative Computing Group in the Nanoscale Device Characterization Division of the Physical Measurement Laboratory (PML). He received a M.S./B.S. in Physics from Yale University, and M.S. and Ph.D. degrees in Physics from Cornell University. Following postdoctoral research at AT&T Bell Laboratories, he joined the research staff at NIST. Mark's research, published in over 145 papers, has focused on the development of a variety of theoretical methods for predicting the properties of magnetic nanostructures and has recently shifted to neuromorphic computing. He has helped organize numerous conferences and has served the American Physical Society on the Executive Committee of the Division of Condensed Matter Physics and as Chair and on the Executive Committee of the Topical Group on Magnetism. He has also served as a Divisional Associate Editor for Physical Review Letters, served on the Editorial Board of Physical Review Applied, and is an Associate Editor for Reviews of Modern physics. Mark is a Fellow of the American Physical Society and has been awarded the Silver Medal from the Department of Commerce.

Projects

Selected Publications

Publications

Coherent spin pumping in a strongly coupled magnon-magnon hybrid system

Author(s)
Yi Li, Wei Cao, Vivek P. Amin, Zhizhi Zhang, Jonathan Gibbons, Joseph Sklenar, John Pearson, Paul M. Haney, Mark D. Stiles, William E. Bailey, Valentine Novosad, Axel Hoffmann, Wei Zhang
We have experimentally identified coherent spin pumping acting as a dampinglike coupling in the magnon-magnon hybrid modes of permalloy/yttrium iron garnet (Py

Temporal pattern recognition with delayed feedback spin-torque nano-oscillators

Author(s)
Mathieu Riou, Jacob Torrejon, B. Garitaine, Flavio Abreu Araujo, Paolo Bortolotti, Vincent Cros, Sumito Tsunegi, K. Yakushiji, Akio Fukushima, Hitoshi Kubota, Shinji Yuasa, Damien Querlioz, Mark D. Stiles, Julie Grollier
The recent demonstration of neuromorphic computing with spin-torque nano-oscillators has opened a path to energy efficient data processing. The success of this
Created October 9, 2019, Updated March 2, 2020