课题基金 / 基金详情

CAREER: HayaRupu: Accelerating Natural Hazard Engineering with AI-Driven Discovery Loops

CAREER: HayaRupu: Accelerating Natural Hazard Engineering with AI-Driven Discovery Loops
职业:HayaRupu:利用人工智能驱动的发现循环加速自然灾害工程
批准号:
2339678
负责人:
Krishna Kumar
金额:
$50.0万
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2024
资助国家:
美国
项目状态:
未结题
起止时间:
2024-08-01 至 2029-07-31

项目摘要

项目成果

Krishna Kumar的其他基金

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中文摘要
翻译
hayaruu项目旨在通过人工智能(AI)加速工程和科学研究的进步,将滑坡灾害作为一个关键的示范领域。该计划的核心是人工智能加速科学发现循环,这是一个将人工智能集成到科学探究的每个阶段的框架,从知识发现到假设检验和建模。这种方法利用机器学习(ML)进行复杂的模式识别和异常检测,从而能够从复杂的数据集中提取新的见解。HayaRupu的一个重要重点是通过构建上下文感知的知识图谱来识别和解决自然灾害工程中的知识差距。此外,该项目通过将人工智能集成到数值模拟中进行创新,利用人工智能的速度和数值模拟的准确性来开发新的优化策略。物理感知的人工智能方法弥合了模拟环境和现实世界应用之间的差距。HayaRupu的方法证明了物理感知的人工智能如何加速科学进步。HayaRupu的一个关键方面是它的教育推广,包括为工程专业的学生创造新的人工智能辅助的可扩展和个性化学习。这一教育计划支持培养具有尖端人工智能技术技能的未来工程师,增强STEM领域的多样性,并为熟练的人工智能和自然灾害工程相结合的劳动力做出贡献。HayaRupu框架(日语为FastLoop)将通过应用人工智能(AI)来促进知识发现,加速自然灾害工程(NHE)的发现,并通过物理感知人工智能技术加速下一代人工智能嵌入式仿真工具进行百亿亿次模拟。这项工作提供了新的人工智能解决方案,以加速自然灾害工程的发现。它有三个关键的智力优势:(i)情景感知知识图作为推理引擎,以实现新的数据驱动发现,并通过几何深度学习推导基本的多尺度方程;(ii)构建NextGen人工智能加速可微模拟器,为解决逆问题和设计问题提供新的范例;(iii)创建一个集成框架,支持大型语言模型的强大的端到端自动化工作流设计,以展示人工智能在推动科学进步方面的潜力。海雅茹正在开发一款个性化的、可扩展的人工智能导师,通过为未来的工程师提供个性化的学习环境、测验和支持,来改变工程教育。主要的教育推广计划包括在奥斯汀公共图书馆组织青少年代码俱乐部,以促进年轻学习者的计算和人工智能素养,并在低收入和代表性不足的社区提供有针对性的项目。此外,该项目还与Code@TACC项目合作,激励高中生,特别是那些来自边缘背景的高中生,从事STEM职业。通过这些努力,海雅鲁普促进了对科学的理解,并在科技教育中营造了一个多元化和包容性的环境。该奖项反映了美国国家科学基金会的法定使命,并通过使用基金会的知识价值和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
The HayaRupu project aims to accelerate advancements in engineering and scientific research through artificial intelligence (AI), utilizing landslide hazards as a key area for demonstration. Central to this initiative is the AI-accelerated scientific discovery loop, a framework that integrates AI into every stage of scientific inquiry, from knowledge discovery to hypothesis testing and modeling. This approach leverages machine learning (ML) for sophisticated pattern recognition and anomaly detection, enabling the extraction of new insights from complex datasets. A significant focus of HayaRupu is identifying and addressing knowledge gaps in natural hazard engineering by building a context-aware knowledge graph. Furthermore, the project innovates by integrating AI in numerical simulations, exploiting the speed of AI and the accuracy of numerical simulations to develop novel optimization strategies. The physics-aware AI methods bridge the gap between simulated environments and real-world applications. HayaRupu's approach exemplifies how physics-aware AI can accelerate scientific progress. A key aspect of HayaRupu is its educational outreach, which involves creating new AI-assisted scalable and personalized learning for engineering students. This educational initiative supports the development of future engineers with skills in cutting-edge AI technologies, enhancing diversity in STEM fields and contributing to a skilled workforce adept in integrating AI and natural hazard engineering.The HayaRupu framework (Japanese for FastLoop) will accelerate discoveries in natural hazards engineering (NHE) by applying Artificial Intelligence (AI) to facilitate knowledge discovery and accelerate NextGen AI-embedded simulation tools for exascale simulations through physics-aware AI techniques. The work provides novel AI solutions to accelerate discoveries in natural hazard engineering. It has three key intellectual merits: (i) context-aware knowledge graphs as reasoning engines to enable new data-driven discoveries and derive fundamental multi-scale equations through geometric deep learning, (ii) building the NextGen AI-accelerated differentiable simulators offering a new paradigm for solving inverse and design problems, (iii) creating an integrated framework of Large Language Model-enabled robust end-to-end automated workflow design to demonstrate the potential of AI in driving scientific advances. HayaRupu is developing a personalized and scalable AI tutor to transform engineering education by offering future engineers a personalized learning environment, quizzes, and support. Key educational outreach initiatives include organizing Tween Code Clubs at the Austin Public Library to promote computational and AI literacy among young learners and offering targeted programs in low-income and underrepresented communities. Additionally, the project collaborates with the Code@TACC program to inspire high school students, especially those from marginalized backgrounds, towards STEM careers. Through these efforts, HayaRupu advances scientific understanding and fosters a diverse and inclusive environment in science and technology education.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.
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SCIPE: Chishiki.ai: A sustainable, diverse, and integrated CIP community for Artificial Intelligence in Civil and Environmental Engineering
  • 批准号:
    2321040
  • 项目类别:
    Standard Grant
  • 资助金额:
    $699.93万
  • 财政年份:
    2023
  • 负责人:
    Krishna Kumar
  • 依托单位:
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  • 批准号:
    2229702
  • 项目类别:
    Standard Grant
  • 资助金额:
    $28.76万
  • 财政年份:
    2022
  • 负责人:
    Krishna Kumar
  • 依托单位:
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  • 批准号:
    2013142
  • 项目类别:
    Continuing Grant
  • 资助金额:
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  • 财政年份:
    2021
  • 负责人:
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  • 依托单位:
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  • 批准号:
    2103937
  • 项目类别:
    Standard Grant
  • 资助金额:
    $55.63万
  • 财政年份:
    2021
  • 负责人:
    Krishna Kumar
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