CyberTraining: Implementation: Medium: Computational Materials Science Summer School - Fostering Accelerated Scientific Techniques (CMS3-FAST)

Texas A&M Engineering Experiment Station, College Station TX

Investigators

Abstract

Advancing Materials Science and Engineering (MSE) is not only important but critical for discovering innovative and sustainable solutions to some of the most pressing challenges facing our society today. The integration of Computational Materials Science (CMS) and Machine Learning (ML)/Artificial Intelligence (AI) techniques, along with Accelerated High-Performance Computing (AHPC) achieved using modern hardware accelerators, can provide a powerful platform for researchers to accelerate advancements in MSE. However, the rapid advancement of these fields has also created a knowledge gap in the workforce, with a shortage of professionals who are simultaneously trained in all three areas: CMS, ML/AI, and AHPC. This project is a beyond-state-of-the-art workforce development program that will integrate CMS, ML/AI techniques, and AHPC into one comprehensive education and hands-on training program to drive transformative fundamental research in MSE. The project will utilize immersive visualization through Virtual and Augmented Reality (VR/AR) tools and AI-based natural language generation tools to provide a tailored environment for participants with different backgrounds and learning styles. The education and hands-on training components of this project are both hybrid and expansive, allowing for large-scale workforce development. In addition, the project will develop studio-based curricula that integrate CMS, ML/AI techniques, and AHPC at various levels of complexity for both undergraduate and graduate students. It will establish partnerships with national laboratories, other academic institutions, and a large network of CMS and CI professionals and contributors. These collaborations will promote a collective impact on training-based workforce development and advancements in MSE. The program also aims to introduce immersive visualization and materials informatics in CMS to K-12 students to promote and encourage their interest in pursuing higher education in related fields. The specific objectives of this project are to: (i) Integrate CMS, ML/AI techniques, and AHPC into one comprehensive education and hands-on training program. (ii) Leverage immersive visualization through VR/AR tools and AI-based natural language generation tools to provide a tailored environment to participants with different backgrounds and learning styles. (iii) Rigorously test and enhance the scaling of the education and hands-on training components, while also broadening access to enable large-scale and unrestricted workforce development. (iv) Develop studio-based curricula that integrate CMS, ML/AI techniques, and AHPC at various levels of complexity for both undergraduate and graduate students. (v) Expand the current network of CI professionals and contributors to establish a powerful platform that accelerates advancements in MSE through continuous training and development. By achieving these objectives, this project will create a new generation of highly skilled CI users, equipped with cutting-edge tools and techniques to drive innovation in MSE. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Civil, Mechanical and Manufacturing Innovation within the Directorate for Engineering. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.