In this episode, Dr. Bryce Meredig and Prof. Mauro discuss:
- Prof. Mauro’s early interest in computer programming, and how that shaped his career
- Challenges and opportunities for applying data-driven modeling techniques, like machine learning, to materials development
- Keys to a successful cross-functional materials research and development team
- The importance of a data-driven culture and strategy for commercial success
- How to bridge skill gaps within materials science through education, curriculum development, and collaborative research
“A company that has a data-driven culture is going to be much more effective at developing better products, faster, and at a lower cost. [This culture] will be essential for their long-term survival.” — Prof. John Mauro
Prof. John Mauro: After earning his PhD in glass science from Alfred University, Prof. John Mauro joined Corning Incorporated, where he eventually became the senior research manager of the Glass Research Department. He is the inventor or co-inventor of several new glass compositions for Corning, including Corning Gorilla® Glass products.
Dr. Mauro joined the faculty at Pennsylvania State University in 2017 and is currently a world-recognized expert in fundamental and applied glass science, statistical mechanics, computational and condensed matter physics, thermodynamics, and the topology of disordered networks.
He is the inventor of new models for supercooled liquid and glass viscosity, glass structure and topology, relaxation behavior, and thermal and mechanical properties. He is the author of more than 200 peer-reviewed publications and has given more than 200 presentations at international conferences and seminars. In addition, he is editor of the Journal of the American Ceramic Society.
Dr. Bryce Meredig, Chief Science Officer and co-founder of Citrine Informatics, researches the application of machine learning to materials science. He earned his PhD in materials science from Northwestern University, where he focused on materials informatics, and his BAS and MBA at Stanford University, where he is also on the faculty of the Department of Materials Science and Engineering. He is the author of more than 20 peer-reviewed publications, including some of the earliest on applying machine learning (ML) to materials development. He was an Arjay Miller Scholar and Terman Fellow at Stanford, and a Presidential Fellow and NDSEG Fellow at Northwestern.
Connect with Dr. Bryce Meredig:
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