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Title: The Role of Machine Learning in Materials and Chemical Discovery
Presenter: Dr. Matthew G. Panthani
Abstract: It is approaching a decade since the White House announced the Materials Genome Initiative (MGI), where materials scientists were asked to find ways to accelerate materials discovery. This initiative has prompted enormous efforts in high-throughput computational simulation and combinatorial experimentation, but we are still far from the lofty MGI goal. However, the emerging field of Materials Informatics could be a new and under-utilized approach that approaches this problem using machine learning. This talk will talk about some recent approaches that have been used to discover new materials with desirable properties, as well as obstacles that are holding this field back.
Bio: Matthew G. Panthani is an Assistant Professor and Herbert L. Stiles Faculty Fellow in the Department of Chemical Engineering at Iowa State University. He obtained a B.S. in Chemical Engineering at Case Western Reserve University and earned his Ph.D. in Chemical Engineering at the University of Texas at Austin under the direction of Prof. Brian A. Korgel. Prior to joining ISU, he was a postdoctoral fellow at the University of Chicago. His research focuses on the synthesis and characterization of new semiconducting materials for electronic and optoelectronic applications. He has received an Air Force Office of Scientific Research Young Investigator Award (2017) and the National Science Foundation Early CAREER Development Award (2019). He has published 37 peer-reviewed journal articles holds 3 U.S. patents.