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

网络培训：实施：媒介：计算材料科学暑期学校 - 促进加速科学技术 (CMS3-FAST)

• 批准号: 2321005
• 负责人: Ankit Srivastava
• 金额: $ 98.32万
• 依托单位: Texas A&M Engineering Experiment Station
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2027-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2321005&HistoricalAwards=false
• 关键词: CyberTraining; Implementation; Medium; Computational; Materials

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.

推进材料科学与工程（MSE）不仅重要，而且对于发现创新和可持续的解决方案来应对当今社会面临的一些最紧迫的挑战至关重要。计算材料科学（CMS）和机器学习（ML）/人工智能（AI）技术的集成，沿着使用现代硬件加速器实现的加速高性能计算（AHPC），可以为研究人员提供一个强大的平台，以加速MSE的进步。然而，这些领域的快速发展也造成了劳动力的知识缺口，缺乏同时接受CMS、ML/AI和AHPC这三个领域培训的专业人员。该项目是一个超越最先进的劳动力发展计划，将CMS，ML/AI技术和AHPC集成到一个综合的教育和实践培训计划中，以推动MSE的变革性基础研究。该项目将通过虚拟和增强现实（VR/AR）工具和基于AI的自然语言生成工具利用沉浸式可视化，为具有不同背景和学习风格的参与者提供量身定制的环境。该项目的教育和实践培训部分是混合和扩展的，允许大规模的劳动力发展。此外，该项目还将开发基于工作室的课程，为本科生和研究生提供各种复杂程度的CMS、ML/AI技术和AHPC。它将与国家实验室，其他学术机构以及CMS和CI专业人员和贡献者的大型网络建立伙伴关系。这些合作将促进对基于培训的劳动力发展和中小企业进步的集体影响。该计划还旨在向K-12学生介绍CMS中的沉浸式可视化和材料信息学，以促进和鼓励他们在相关领域接受高等教育的兴趣。该项目的具体目标是：（i）将CMS，ML/AI技术和AHPC集成到一个全面的教育和实践培训计划中。(ii)通过VR/AR工具和基于AI的自然语言生成工具利用沉浸式可视化，为具有不同背景和学习风格的参与者提供量身定制的环境。(iii)严格测试和加强教育和实践培训部分的规模，同时扩大获得机会，以实现大规模和不受限制的劳动力发展。(iv)开发基于工作室的课程，为本科生和研究生在各种复杂程度上集成CMS，ML/AI技术和AHPC。(v)扩大CI专业人员和贡献者的现有网络，建立一个强大的平台，通过持续的培训和发展加速MSE的进步。通过实现这些目标，该项目将创造新一代高技能的CI用户，配备先进的工具和技术，以推动MSE的创新。高级网络基础设施办公室的这一奖项得到了民用部门的共同支持，工程理事会内的机械和制造创新。该奖项反映了NSF的法定使命，并通过评估被认为值得支持使用基金会的知识价值和更广泛的影响审查标准。