Neuromorphic Engineering & Computational Neuroscience

Charles M. Higgins

Associate Professor of Neuroscience & Electrical/Computer Engineering

The University of Arizona  ·  Tucson, Arizona

"My driving interest is building truly intelligent machines — machines that see, think, and act like living things."
Insect Vision Neuromorphic Engineering Biologically-Inspired Robotics Bat Echolocation models Computational Neuroscience Artificial Intelligence
cmh@arizona.edu
(520) 621-6604
Gould-Simpson 430
Professor Charles M. Higgins
Inspiration
The original Star Trek TV show in the 1970's inspired the young Charles Higgins to pursue a career combining engineering, computers, neuroscience, and robotics.
Insect Robots
Artificial Intelligence
Insect Electrophysiology
Bat Echolocation models
Bat-brain UAVs

Where Biology Meets Engineering

Charles Higgins is an Associate Professor in the Department of Neuroscience with a joint appointment in Electrical and Computer Engineering at the University of Arizona, which he joined in 1999. He holds additional appointments in Applied Mathematics, Entomology/Insect Science, and the BIO5 Institute.

Though he started his career as an electrical engineer — earning his Ph.D. from Caltech in 1993 — his fascination with the natural world led him to study insect vision, visual processing, and the intersection of robotics and biology. His driving interest remains building truly intelligent machines: machines that can see, navigate, and interact with the world as elegantly as living organisms shaped by millions of years of evolution.

His laboratory conducts research spanning computational neuroscience to biologically-inspired engineering. The unifying goal is to understand the representations and computational architectures used by biological systems — architectures that are often functionally superior to conventional engineered solutions. Projects are conducted in close collaboration with "wet" neurobiology laboratories performing anatomical, electrophysiological, and histological studies, often on insects.

Dr. Higgins has received numerous teaching awards and was honored from 2013 to 2017 as a member of the Nifty Fifty: a group of elite scientists chosen to share the excitement of science with schoolchildren. He has also been recognized as a "Leading Edge" researcher and a da Vinci Fellow, and gave a widely publicized TEDxTucson talk in 2013.

Dr. Higgins' work has garnered extensive media coverage, including television, radio, and newspaper features worldwide. A landmark demonstration — a robot guided by the live eyes and brain of a moth — captured international headlines and exemplified his lab's signature approach: harnessing biological intelligence to solve engineering problems.

1999 – Present
Associate Professor
Neuroscience & Electrical Engineering
University of Arizona · Tucson, AZ
1996 – 1999
Postdoctoral Fellow (Advisor: Christof Koch)
Division of Biology, Caltech · Pasadena, CA
1993 – 1996
Staff Member, Radar Systems
MIT Lincoln Laboratory · Lexington, MA
1993
Ph.D., Electrical & Computer Engineering
California Institute of Technology · Pasadena, CA
1989
M.S., Electrical & Computer Engineering
Georgia Institute of Technology · Atlanta, GA
1987-1990
Summer supplementary staff member
IBM Cambridge Scientific Center· Cambridge, MA
1987
B.S., Electrical & Computer Engineering
Louisiana State University · Baton Rouge, LA
1986
Study Abroad
Queen Mary College, University of London, England

Areas of Fascination

Insect Vision & Motion Detection
Studying flies, bumblebees, and dragonflies to understand how evolution produced exquisite visual motion systems — and reverse-engineering them into silicon.
Computational Neuroscience
Mathematical and computational modeling of neural systems — from biophysical ion-channel models to abstract network architectures — to understand how the brain computes.
Autonomous Aerial Robotics
Developing UAV navigation systems using neuromorphic vision — self-motion estimation, obstacle avoidance, and target tracking inspired by insect flight control.
Neuromorphic VLSI
Building analog VLSI chips whose architectures directly mimic neuronal circuits — highly efficient, massively parallel motion processing hardware inspired by living visual systems.
Artificial Intelligence
Building intelligent machines from first principles — applying deep insights from neuroscience to modern AI architectures including models of cognition and human sleep.
Bat Echolocation models
Bio-inspired sonar navigation drawing on bat echolocation for simultaneous localization and mapping — enabling robots to build accurate 3D maps from acoustic echoes alone.