Faculty

Bingni Brunton
bbruntoncs.washington.edu
Adjunct, Biology
Computational Neuroscience
Data-driven models for neuroscience and efficient algorithms for neuroengineering
Matthew Golub
CSE 528
mgolubcs.washington.edu
Artificial Intelligence, Computational Neuroscience, Data Science, Data Management & Visualization, Machine Learning
Machine learning and data science for neuroengineering and basic systems neuroscience; deep learning techniques for understanding neural computations in the brain; brain-computer interfaces
Jeffrey Herron
jeffherruw.edu
Adjunct, Neurological Surgery
Computational Neuroscience
Brain-computer interfaces, neural engineering, computational neuroscience, cyberphysical systems, software interfaces for human-use neuromodulation research tools
Rajesh P. N. Rao
raocs.washington.edu
Artificial Intelligence, Computational Neuroscience, Machine Learning, Robotics

Computational neuroscience, artificial intelligence, brain-computer interfaces

Andrea Stocco
stoccou.washington.edu
Adjunct, Psychology
Computational Neuroscience
Human use of abstract mental representations (like, rules, instructions, and plans) to perform complex tasks

Graduate Students (CSE)

Preston Jiang
CSE 374
prestonjcs.washington.edu
Computational Neuroscience, Machine Learning
Computational neuroscience
Lillian Li
CSE 306
yli2244cs.washington.edu
Artificial Intelligence, Computational Neuroscience, Machine Learning
Zoe Steine-Hanson
zsteinehcs.washington.edu
Neural Engineering, Neural Decoding
Computational Neuroscience
Gabrielle Strandquist
gsquistcs.washington.edu
Neural Engineering
Computational Neuroscience

Undergraduate Researchers

Matthew Bryan
CSE 286
mmattbcs.washington.edu
Brain-Computer Interfaces, Neural Engineering
Artificial Intelligence, Computational Neuroscience, Machine Learning
Application of machine learning techniques to the brain-computer interface (BCI) domain. This includes hierarchical task modelling (HBCIs), and the use of POMDPs for optimal data collection.