Matthew D. Golub, PhD

Assistant Professor, Paul G. Allen School of Computer Science and Engineering
Theory Faculty, UW Computational Neuroscience Center
Training Faculty, UW Graduate Program in Neuroscience
Affiliate Investigator, Allen Institute for Neural Dynamics

My research group focuses on the intersection of neuroscience, neuroengineering, machine learning, and data science. We develop computational models and algorithms for understanding how single-trial neural population activity drives our abilities to generate movements, make decisions, and learn from experience.

Previously, I was a Postdoctoral Fellow in the Department of Electrical Engineering at Stanford University, where I was jointly advised by Professors Krishna Shenoy (EE, BioE & Neurobiology; Stanford & HHMI), Bill Newsome (Stanford Neurobiology), and David Sussillo (Stanford EE & Facebook Reality Labs). My postdoctoral work was focused on developing deep learning techniques for understanding population-level neural computations underlying perceptual decision making in the brain. This work was recognized by a K99/R00 Pathway to Independence Award from the National Institutes of Health.

I completed my PhD at Carnegie Mellon University, where I was jointly advised by Professors Byron Yu and Steve Chase. There, I developed brain-computer interfaces as a scientific paradigm for investigating the neural bases of learning and feedback motor control. My dissertation, titled "Interpreting neural population activity during feedback motor control," was awarded the A.G. Milnes Best Thesis Award by the Department of Electrical & Computer Engineering.


For scheduling purposes, I share my calendar availability here.

Office: CSE 528
Paul G. Allen Center
185 E Stevens Way NE
Seattle, WA 98195-2350