Brian DeCost is a materials research engineer in the Data and AI Driven Materials Science Group at the National Institute of Standards and Technology. He earned a B.S. in Chemical Engineering at the University of Florida and a Ph.D. in Materials Science and Engineering at Carnegie Mellon University. Brian’s research focuses on developing and applying scientific machine learning methods and automation tools to address fundamental and applied problems in microstructure science and alloy design, with a particular focus on active learning for autonomous experiment planning and execution.
postdoctoral opportunity: Scientific machine learning methods for trustable accelerated materials characterization and design