Data Science Institute Seed Grants Support to EE Prof. James Anderson and Team
January 19, 2021
The Data Science Institute’s Seed Funds Program supports new collaborations that will lead to longer term and deeper relationships among faculty in different disciplines across campus. Aimed at advancing research that combines data science expertise with domain expertise, funded research should embody the spirit of the Institute’s mission statement. The following research projects and teams have received 2021 awards.
Randomized Methods for High-Throughput Characterization of Tokamak Sensor Streams
James Anderson, Electrical Engineering
Michael Mauel, Applied Physics
Jeffrey Levesque, Applied Physics
Fusion science seeks to advance our fundamental understanding of physics and make plasma fusion viable for applications such as clean energy production. Tokamak fusion reactors generate vast and rich data sets obtained through multiple sensing modalities. The goal of this project is to develop new robust and efficient methods rooted in randomized numerical linear algebra for analyzing and characterizing complex fusion discharge dynamics.