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Kurtis Cantley

By: Sherry Squires   Published 7:29 am / May 5, 2017

Kurtis Cantley

Kurtis Cantley

Assistant Professor
Electrical and Computer Engineering

Kurtis Cantley is exploring artificial neural networks for future computing systems that can learn and adapt. His most recent award is a three-year, $322,866 grant from the Defense Threat Reduction Agency (DTRA) to study the impact of radiation exposure on pattern recognition in memristor-based neuromorphic circuits.

According to Cantley, “electronic neural networks are able to solve many complex problems and perform cognitive tasks much more efficiently than digital systems. They are also expected to be more robust and reliable than traditional computing solutions.” However, there is very little research to date that quantifies how defect-tolerant these neuromorphic circuits might actually be.

This project is focused on understanding how radiation affects learning behavior and pattern recognition capability in circuits with memristive synapses. Cantley’s goal is to develop a robust modeling and simulation platform that accounts for physical changes caused by many different types of radiation profiles. A primary outcome will then be to provide best-practice recommendations regarding device and circuit design to mitigate threats posed by radiation exposure.

“It is exciting to see the ground breaking research going on here at Boise State,” said Mark Rudin, associate vice president for Research and Economic Development. “I’m proud to be part of a university that continues to innovate in science and engineering.”

This is Cantley’s second Young Investigator award, after receiving a grant from the Air Force Office of Scientific Research (AFOSR) in 2014. For more about Cantley and his research, visit

The project or effort depicted was or is sponsored by the Department of the Defense, Defense Threat Reduction Agency. The content of the information does not necessarily reflect the position or the policy of the federal government, and no official endorsement should be inferred.