Discovering characteristics of materials using machine learning will be the subject of the first Center for Artificial Intelligence Foundations and Scientific Applications (CENSAI) monthly seminar of the fall 2022 semester. The talk will be held online at 4 p.m., Sept. 12, and is open to the Penn State community.
A. Gilad Kusne, staff scientist with the ³Ô¹ÏÍøÕ¾ Institute of Standards and Technology (NIST), adjunct professor at the University of Maryland, and a fellow of the American Physical Society, will give a talk on his research that is part of the White House’s Materials Genome Initiative (MGI) at NIST. The MGI’s purpose is to drive the exploration and innovation of advanced materials through machine learning.
In his presentation, Kusne will detail the systems in development at NIST that use machine learning to facilitate steps of the research process, such as designing, executing and analyzing experiments. This approach is designed to accelerate the search for knowledge while reducing burdens on scientists.
Kusne received his bachelor’s, master’s and doctoral degrees from Carnegie Mellon University. His research emphasizes building autonomous research systems with machine learning with the aim of advancing biological materials. Kusne currently leads the development of international, cross-disciplinary autonomous research systems with a focus on improving solid state, soft, and biological materials. These research systems, coupled with machine learning, allow the design and execution (in the lab and in silico), for further analysis. His work has earned him the highest NIST award, the NIST Bronze Award.
CENSAI is housed in the Institute for Computational and Data Sciences (ICDS) and enables Penn State researchers to explore the use of artificial intelligence as a tool to dramatically accelerate the scientific process.
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