The Michigan Institute for Computational Discovery and Engineering has awarded its first round of Catalyst Grants, providing $75,000 each to four innovative projects in computational science. The proposals were judged on novelty, likelihood of success, potential for external funding, and potential to leverage U-M’s existing computing resources.
Catalyst grants are available to support a range of relatively short-term, small-scale collaborative activities. Catalyst grants are intended to help better define an issue or decision maker needs, gather resources and develop partnerships, and determine next steps. Activities may include, but are not limited to, convening workshops or a conference, preparing white papers, and project planning for larger collaborative projects that would be eligible for transformation grants or other funding opportunities.
Funded projects:
- From Spiking Patterns to Memory formation — Tools for Analysis and Modeling of Network-wide Cognitive Dynamics of the Brain. Researchers: Sara Aton, Department of Molecular, Cellular and Developmental Biology and Michal Zochowski, Department of Physics, Biophysics Program. The aim of the research is to develop models as well as analysis tools to understand network-wide spatio-temporal patterning underlying experimentally observed neural spiking activity. The research team has developed novel tools to analyze dynamics of neuronal representations across time, before during and after learning. These tools, for the first time, compare the stability of network dynamics before and after memory encoding.
- Integral Equation Based Methods for Scientific Computing. Researchers: Robert Krasny, Department of Mathematics. This project expands the application of numerical methods in which the differential equation is first converted into an integral equation by convolution with the Green’s function, followed by discretization and linear solution. Recent advances in numerical analysis and computing resources make this expansion possible, and the research team believes that integral equation-based numerical methods are superior to traditional methods in both serial and parallel computations. The project will attempt to apply these numerical methods to studies of viscous fluid flow, protein/solvent electrostatics, and electronic structure.
- Computational Energy Systems. Researchers: Pascal Van Hentenryck, Industrial and Operations Engineering (IOE); E. Byon, IOE; R. Jiang, IOE; J. Lee, IOE; and J. Mathieu, Electrical Engineering and Computer Science. The research team aims to develop new algorithms for the U.S. electrical power grid that integrate renewable energy sources, electrification of transportation systems, the increasing frequency of extreme weather events, and other emerging contingencies.
- Black Swans, Dragon Kings, and the Science of Rare Events: Problems for the Exascale Era and Beyond. Researchers: Venkat Raman, Aerospace Engineering; Jacqueline Chen, Sandia National Laboratory; and Ramanan Sankaran, Oak Ridge National Laboratory. The purpose of the project is to develop the computational frameworks for exploring the tails of distributions, which lead to rare but consequential (and often catastrophic) outcomes. Two such rare events are “Black Swans” (occurring from pre-existing but unencountered events) and “Dragon Kings (occurring due to an external shock to the system). The methods developed are expected to have application in aerospace sciences, power generation and utilization, chemical processing, weather prediction, computational chemistry, and other fields.
Another round of Catalyst Grants will be awarded next year.
