Michal Zochowski is a Professor in the Departments of Physics and Biophysics Program. His research interests lie in the intersection of physics and neuroscience. His group focuses on understanding the mechanisms of the formation of spatio-temporal patterns in coupled dynamical systems, their applicability and role during information processing in the brain. They use theoretical and experimental approaches, including computational modeling of various brain processes including memory storage, consolidation and its retrieval.
Charles Doering is the Nicholas D. Kazarinoff Collegiate Professor of Complex Systems, Mathematics and Physics and the Director of the Center for the Study of Complex Systems. He is a Fellow of the American Physical Society, and a Fellow of the Society of Industrial and Applied Mathematics (SIAM). He uses stochastic, dynamical systems arising in biology, chemistry and physics models, as well as systems of nonlinear partial differential equations to extract reliable, rigorous and useful predictions. His research spans rigorous estimation, numerical simulations and abstract functional and probabilistic analysis.
His research focuses on understanding the role of strong correction effects in many-body quantum systems. The objective is to discover novel quantum states/materials and to understand their exotic properties using theoretical/numerical methods (with emphasis on topological properties). In his research, numerical techniques are applied to resolve the fate of a quantum material (or a theoretical model) in the presence of multiple competing ground states and to provide quantitative guidance for further (experimental/theoretical) investigations.
Shawn McKee is a Research Scientist in the Department of Physics, and the Director of MICDE’s Center for Network and Storage-Enabled Collaborative Computational Science.
He is also the U-M site director for ATLAS Great Lakes Tier 2, which provides 4,000 CPUs cores and 3.5 petabytes of storage for ATLAS physics computing. McKee’s research interests are mainly in two parts: using the ATLAS detector to search for Dark-Matter (assuming it has a particle physics origin; and researching distributed data-intensive infrastructures to improve their ability to support high-energy physics and similar distributed e-Science efforts.