
About
Stephen Keeley is an Assistant Professor in the Department of Natural Sciences at Fordham University, where he leads the Keeley Lab focused on machine learning and computational neuroscience. His research develops statistical methods for analyzing neural processing and behavior using datasets from various animal models.
Education
- Ph.D. in Neural Science from New York University
- Postdoctoral training at Princeton University
- Bachelor's degrees in Physics and Neuroscience from University of Rochester
Research Focus
His lab specializes in:
- Latent variable models for neural dynamics
- Dimensionality reduction techniques
- Multi-region neural communication
- Bayesian methods for spike train data
- Human and animal decision-making processes
Teaching
Courses include Research Design & Analysis, Biological Modeling, and Machine Learning Methods for Neural Data.
Lab & Team
Leads an active research group collaborating with international institutes. Current research involves neural dynamical systems and high-dimensional psychophysics with Reality Labs Research.
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