October 27–29, 2025

Online Course

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Artificial intelligence (AI) attracts the interest of scientists and engineers, entrepreneurs and government leaders, and researchers and educators. Within the study of materials science and engineering and related manufacturing processes, in particular, there has been an explosion of new research, publications and symposia. Through the Artificial Intelligence in Materials Science and Engineering course, participants will benefit from the guidance of team of experts to gain an overview, learn about importance developments in AI, and the impact of AI on materials science and engineering and related manufacturing processes. Attendees will build upon their understanding of how AI can help to accelerate processes, reduce costs, and innovate products.

Who Should Take This Course

Anyone involved in AI projects and wishes to gain practical insight and knowledge, including industry professionals, researchers, and university students, as well as leaders and managers who would like to have a deeper understanding of AI in materials science and engineering and related manufacturing processes

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Course Sponsors and Organizers

This course is sponsored by the TMS Computational Materials Science and Engineering Committee, the TMS Professional Development Committee, and the TMS Artificial Intelligence Subcommittee of the Materials Innovation Committee. This course is being organized by the following individuals:

Instructors

• Benjamin Afflerbach, University of Wisconsin
• Ankit Agrawal, Northwestern University
• Raymundo Arroyave, Texas A&M University
• Mukil Venthan Ayyasamy, GE Aerospace Research
• Ryan Jacobs, University of Wisconsin
• Benji Maruyama, U.S. Air Force Research Laboratory
• Dane Morgan, University of Wisconsin
• Ghanshyam Pilania, GE Aerospace Research

Go to the Instructors page to view bios and learn more about their research and professional experience.