Connor Bybee

Reveal Contact Info

PhD Student

Computational Biology

Sommer Lab

Current Research

My goals are to gain insight into the physics of computation in nervous systems in order to construct both efficient computers and intelligent learning algorithms. In addition, I seek to use current knowledge of electrical circuits and statistical learning to understand the function of neural circuits and intelligent behavior. Currently, the non-linear activity and branching architecture of dendrites has motivated me to investigate the high-order statistics in natural images.


I received a BS in Chemical Engineering from the University of Kansas, after which I studied Computer Engineering, receiving an MS from the University of Southern California in 2015. My research focused on bio-inspired or neuromorphic computer micro-architectures and how learning algorithms could be mapped to bio-inspired circuits.