What You Will Learn
By the end of this course, attendees will be able to:
- Create, critically evaluate, and interpret machine learning models for materials
- Describe how machine learning can positively impact their work as scientists
- Organize their data in a way that’s suitable for machine learning
- Design an experiment that incorporates machine learning, including:
- Create a sequential learning workflow for their experiment
- Predict the properties of an unknown material with a machine learning model
- Develop experimental material candidates that satisfy target conditions/properties
Learn more about this program on the
Course Curriculum page.
Who Will Benefit
Professionals in materials science and engineering who want to learn how to incorporate artificial intelligence (AI) and machine learning (ML) in to their research and/or product development workflows will benefit from attending this course.
Course Sponsors and Organizers
This congress is sponsored by the TMS Materials Processing & Manufacturing Division (MPMD) and the Integrated Computational Materials Engineering (ICME) Committee, and is being organized by the following individuals:
- Bryce Meredig, Lead Organizer, Co-founder and Chief Science Officer, Citrine Informatics
- Erin Antono, Data Scientist, Citrine Informatics
- Brian DeCost, National Institute of Standards and Technology
- Jason Hattrick-Simpers, National Institute of Standards and Technology
- John C. Mauro, Professor of Materials Science and Engineering, Pennsylvania State Univeristy
- Josh Tappan, Community Manager, Citrine Informatics
- Christopher Wolverton, Jerome B. Cohen Professor of Materials Science and Engineering, Northwestern University
Learn more about each instructor, and the expertise they have to offer attendees of this course.
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For More Information
For more information about this meeting, please complete the meeting inquiry form or contact:
TMS Meeting Services
5700 Corporate Drive Suite 750
Pittsburgh, PA 15237
Telephone:
U.S. and Canada Only: 1-800-759-4867
Other Countries: 1-724-776-9000
Fax: 1-724-776-3770