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
Teaching
Neuroscience Graduate Research [NEU 292 - 006]
Neuroscience Research Review [NEU 295 - 032]
Research [PHYSICS 299 - 012]
Introductory Mechanics and Relativity [PHYSICS 5A - 001]
Introduction to Computational Neuroscience [NEU 151 - 001]
Neuroscience Graduate Research [NEU 292 - 006]
Neuroscience Research Review [NEU 295 - 038]
Research [PHYSICS 299 - 013]
Introductory Physics [PHYSICS 8A - 001]
Neuroscience Graduate Research [NEU 292 - 006]
Neuroscience Research Review [NEU 295 - 032]
Research [PHYSICS 299 - 012]
Introductory Mechanics and Relativity [PHYSICS 5A - 001]