Cargando…

A framework for materials informatics education through workshops

ABSTRACT: The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML). In addition to incorporating these topics in undergraduate and graduate curr...

Descripción completa

Detalles Bibliográficos
Autores principales: Mannodi-Kanakkithodi, Arun, McDannald, Austin, Sun, Shijing, Desai, Saaketh, Brown, Keith A., Kusne, A. Gilad
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10153775/
https://www.ncbi.nlm.nih.gov/pubmed/37361859
http://dx.doi.org/10.1557/s43577-023-00531-6
Descripción
Sumario:ABSTRACT: The burgeoning field of materials informatics necessitates a focus on educating the next generation of materials scientists in the concepts of data science, artificial intelligence (AI), and machine learning (ML). In addition to incorporating these topics in undergraduate and graduate curricula, regular hands-on workshops present the most effective medium to initiate researchers to informatics and have them start applying the best AI/ML tools to their own research. With the help of the Materials Research Society (MRS), members of the MRS AI Staging Committee, and a dedicated team of instructors, we successfully conducted workshops covering the essential concepts of AI/ML as applied to materials data, at both the Spring and Fall Meetings in 2022, with plans to make this a regular feature in future meetings. In this article, we discuss the importance of materials informatics education via the lens of these workshops, including details such as learning and implementing specific algorithms, the crucial nuts and bolts of ML, and using competitions to increase interest and participation. GRAPHICAL ABSTRACT: [Image: see text]