MELVILLE, N.Y., Jan. 18, 2024 — Applied Physics Letters and APL Publishing are pleased to announce Jean Anne Incorvia as the winner of the 2023 Rising Stars Award for her work in the development and novel utilization of artificial neural networks.
In the winning paper, “Stochastic domain wall-magnetic tunnel junction artificial neurons for noise-resilient spiking neural networks,” Incorvia and her team constructed an artificial (‘spiking’) neural network based on domain wall-magnetic tunnel junction architecture. The researchers were then able to demonstrate that not only did these magnetic neuron networks have the inherent ability to collect information and fire like real neurons, but they also possessed a tunable stochasticity (randomness) that made them more capable of processing ‘noisy’ data.
“This is brain-inspired,” said Incorvia, “since biological neurons are also stochastic in their firing. These results show the potential benefits of using magnetic neurons for computing. It also shows a space in which this type of neuromorphic computing could be impactful, for situations we expect data will be noisy — such as edge computing.”
An approach to computer engineering that takes its inspiration from the architecture and behavior of the human brain, neuromorphic computing aims to increase efficiency and reduce latency by removing the need for a system to shuttle data back and forth between memory and processing. Neuromorphic edge computing would allow for remote devices to process data internally rather than sending it back to a central network — think, for example, of a smartphone that doesn’t need the cloud.
By demonstrating the behavior of magnetic neurons and their capacity to process noisy data, Incorvia and her team are bringing this revolutionary approach to computing even closer to the forefront.
“Dr. Incorvia’s paper was chosen because it is timely and relevant to the field of spiking neural networks,” said Lesley Cohen, Editor-in-Chief of Applied Physics Letters. “It is an impressive achievement that moves the field closer toward the delivery of energy-efficient, resource-limited hardware for neuromorphic edge computing. We are delighted to award this prize to Dr. Incorvia and her team for an excellent contribution to an important, emerging area of applied physics.”
Incorvia is an Associate Professor in Electrical and Computer Engineering at The University of Texas at Austin, where she directs the Integrated Nano Computing Lab. After receiving her B.S. in Physics from UC Berkeley in 2008 and her Ph.D. in Physics from Harvard University in 2015 while cross-registered at the Massachusetts Institute of Technology, she completed her postdoctoral education at Stanford University from 2015 to 2017.
At the University of Texas at Austin, her research group is focused on leveraging new materials and physics for computing, with a specialized interest in nanomagnetic and low-dimensional materials. She is also on the lookout for other applications of these materials and devices, such as in energy and medicine. She has described herself as being right at home in the crossroads of electrical engineering, computer engineering, materials science, and physics.
She also described herself as “honored” by the “unexpected surprise” of the award.
“It shows the applied physics community’s appreciation of my research group’s efforts to engineer nanomagnetic devices for tackling key computing challenges,” said Incorvia. “The Ph.D. students on the paper worked very hard in nanofabrication, device testing, and neural network modeling, and I appreciate them being recognized in their work.”
The APL Rising Star Award and Collection was established in 2022 to recognize and celebrate the next generation of global scientists who will shape the future of applied physics. A selection committee of APL Editorial Advisory Board members selects the winning paper and finalists for the collection to bring increased visibility to the extraordinary work of early-career principal investigators.
Award winners are invited to write an Applied Physics Letters perspective on their field of expertise and gifted an honorarium of $1,500.
As for what’s next, Incorvia considers unconventional computing with magnetic, low-dimensional, and other emerging materials and devices to be “a wide-open field.”
“I think we are at a good time when the field has matured enough that we have a better idea what makes a ‘good’ neuron, synapse, stochastic bit, probabilistic bit, etcetera,” she said. “I hope to continue to take a holistic approach to understand the circuit, system, and application needs and explore how materials and devices can make system-level impact in energy efficiency or functionality. I also hope to delve more into higher-order functions — inspired by the brain — that these devices can use to aid system-level needs.”
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Applied Physics Letters (APL) features concise, up-to-date reports on significant new findings in applied physics. Emphasizing rapid dissemination of key data and new physical insights, APL offers prompt publication of new experimental and theoretical papers reporting applications of physics phenomena to all branches of science, engineering, and modern technology. In addition to regular articles, the journal also publishes invited Fast Track, Perspectives, and in-depth Editorials which report on cutting-edge areas in applied physics.
ABOUT THE APL RISING STAR AWARD AND COLLECTION
Applied Physics Letters is committed to recognizing the next generation of global scientists who will shape the future of applied physics. The APL Rising Stars Collection and APL Rising Star Award bring visibility to the impressive work of early career principal investigators.
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