Research Expertise and Interest

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

Research Description

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.