معرفی
Matthew Golub is an Assistant Professor at the University of Washington's Allen School of Computer Science & Engineering, where he leads the Systems Neuroscience & AI Lab (SNAIL). He also holds affiliations with the UW Computational Neuroscience Center (Theory Faculty) and the Allen Institute for Neural Dynamics (Affiliate Investigator). His research focuses on the intersection of computational neuroscience, neuroengineering, and machine learning, particularly in understanding how neural population dynamics drive motor control, decision-making, and learning processes.
- Education:
- PhD in Electrical & Computer Engineering from Carnegie Mellon University (2015), awarded the A.G. Milnes Best Thesis Award
- Postdoctoral Fellowship at Stanford University (2017-2022), advised by Krishna Shenoy, Bill Newsome, and David Sussillo
His work develops computational models for analyzing single-trial neural activity, with applications in brain-computer interfaces (BCIs) as tools for basic neuroscience. Recent projects include active learning techniques using two-photon holography, multi-regional latent variable models, and gradient-ascent explanations for local-circuit plasticity. His lab trains PhD students in neuroscience and machine learning across departments.
Scientific awards include the NIH K99/R00 Pathway to Independence Award (2019) and NIH T32 Fellowship for trainees in his lab. He has presented invited talks at institutions including Yale, Berkeley, and the Allen Institute.
Current Lab Members:
- Postdoctoral Fellows: Matthew Bull, Joseph Pemberton, Jacob Sacks
- Graduate Students: Belle Liu, Christina Wang, Lillian Li
- Undergraduate Researchers: Tanya Naveen, Nahush Shrivatsa, Zeynep Toprakbasti
