Kurtis Cantley, Ph.D.

Bio

Dr. Cantley received his Ph.D. in electrical engineering in December 2011 from the University of Texas at Dallas under the supervision of Prof. Eric Vogel. The main focus of his research was fabrication and simulation of novel low-temperature electronic devices for artificial neural systems, the first three years of which were funded by the National Defense Science and Engineering Graduate (NDSEG) fellowship. He also had the opportunity to work on a project centered around chemical and biological sensor FETs and associated detection circuitry as part of his post-doctoral research at UTD. Before moving to Texas, Dr. Cantley received his master’s degree in electrical engineering in 2007 from Purdue University, where his advisor was Prof. Mark Lundstrom. His thesis topic was the simulation of III-V materials in nanoscale transistors to determine their performance potential compared to silicon. While at Purdue, he was heavily involved with the Network for Computational Nanotechnology, and contributed to the deployment of simulation tools with graphical user interfaces on nanohub.org. The majority of his work was upgrading a program called NanoMOS, which subsequently experienced a surge in usage and now has over 94 tool citations in the literature. Prior to Purdue, Dr. Cantley was a student at Washington State University, graduating from the Honors College in 2005. He also obtained minors in math, physics, and music. For two summers while at WSU, Dr. Cantley participated in the National Security Internship Program (NSIP) at Pacific Northwest National Laboratory, near his home town of Kennewick, WA.

Education

PhD Electrical Engineering 2011, University of Texas at Dallas
MS Electrical and Computer Engineering 2007, Purdue University
BS Electrical Engineering with Honors 2005, Washington State University

Research

Research in the Cantley group is broadly focused on the general capabilities and applications of artificial neural networks that mimic biology. These include sensor arrays and the associated detection circuitry, as well as next-generation computation. In 2014, Dr. Cantley received the Young Investigator Award from the Air Force Office of Scientific Research (AFOSR) to develop circuits which learn to recognize temporal patterns within large sets of stimuli without supervision. His students are also working on neural interfaces with collaborators from the materials science and engineering and biology departments at BSU. Eventually, these systems could help replace lost functionality caused by tissue damage, perform diagnostics, apply stimulation, or provide a platform for studies of structure and/or operation. Students in the group are typically expected to learn and apply various fabrication, simulation, and electrical characterization techniques.

Areas of Interest

Neuromorphic engineering, neural systems and interfaces, electronic materials and devices

Kurtis Cantley, Ph.D.

Faculty