In this episode, Dr. Meredig and Dr. Warren discuss:
- How a shared improv background has surprisingly made a positive impact on their scientific careers and technical communication skills.
- The history of the Materials Genome Initiative, its role in the materials innovation ecosystem, and its future outlook.
- Successful models of collaboration between policymakers, national labs, academic research groups, and for-profit companies driving innovation in materials research and development.
- The role the National Institute of Standards and Technology (NIST) plays as a convener and community builder in the field of data-driven materials science.
- The importance of high-quality curated data in a materials R&D ecosystem.
“What people really want to see is the advantage of having a data management plan, and that’s where we’re seeing a change. Now, all you have to do is open a journal to see a lot of high-quality articles on data-driven methods and machine learning for materials discovery, and that’s an easier case to make to the community.” — Dr. Jim Warren
Dr. Jim A. Warren is the Technical Program Director for Materials Genomics in the Material Measurement Laboratory of NIST, where he has been a scientist since 1992. He came to NIST after receiving his PhD in Theoretical Physics at the UC Santa Barbara and his BA (also in Physics) from Dartmouth College. In 1995, Jim co-founded the NIST Center for Theoretical and Computational Materials Science.
Dr. Warren is currently focused on the Materials Genome Initiative, a multi-agency initiative designed to create a new era of policy, resources, and infrastructure that supports U.S. institutions in the effort to discover, design, develop, and deploy advanced materials twice as fast, at a fraction of the cost.
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.
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