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Signal Processing & Machine Learning

Brain function can be characterized by a variety of noisy signals that vary in their spatial and temporal scales. Research in this theme is focused on how to best extract these signals and identify those that are most meaningful for testing hypothesis about brain structure, function, and behavior.

 Affiliated Faculty

Professor
Psychological & Brain Sciences
How biological organisms and artificial intelligent agents visually sense the world and make decisions.
Professor
Psychological & Brain Sciences
Visual attention; Cognitive neuroscience; Brain Imaging; Exercise physiology.
Distinguished Professor
Psychological & Brain Sciences
Professor Grafton is interested in how people organize movement into goal-oriented action.
Associate Professor
Molecular, Cellular, and Developmental Biology
Combining theory and experimentation to understand how navigational decisions arise from neural-circuit computation.
Professor
Electrical and Computer Engineering
Next-generation wireless communication, sensing and inference; Robust, neuro-inspired machine learning.
Professor
Mechanical Engineering
Modeling, dynamics, & control of neural populations; application to neurological disorders such as Parkinson's disease.
Assistant Professor
Molecular, Cellular, and Developmental Biology
Systems neuroscience, neuroethology, genetics. Dissecting neural circuits that control a motor sequence in fruit flies.
Associate Professor
Electrical and Computer Engineering
Exploring neural circuitry and illuminating its function, using new neurotechnology.