Research Bio

Michael DeWeese is a professor in the Department of Neuroscience and the Department of Physics.  His group’s research spans three broad areas: nonequilibrium statistical mechanics, machine learning theory, and systems neuroscience. Their work in these different areas is linked by several unifying ideas, including stochasticity, high dimensionality, non-convex optimization, learning and prediction, and the statistics of natural data. Many of their projects involve inspiration or tools from one of these fields applied to questions from another.

Research Expertise and Interest

machine learning, computation, systems neuroscience, auditory cortex, neural coding, statistical mechanics