IUCRC Phase II Arizona State University: Center for Accelerated Real Time Analytics (CARTA)

IUCRC 第二阶段亚利桑那州立大学：加速实时分析中心 (CARTA)

• 批准号: 2311026
• 负责人: Ming Zhao
• 金额: $ 49.97万
• 依托单位: Arizona State University
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-10-01 至 2028-09-30
• 项目状态: 未结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2311026&HistoricalAwards=false
• 关键词: IUCRC; Phase; II; Arizona; State

Accelerated and real-time analytics is a leading edge of the smart data revolution, pushed by advances in internet-connected sensor hardware on one side and accelerated AI/ML analytics on the other. These technologies include machine learning, cognitive, quantum, neuromorphic, and edge computing combined with new classes of sensory and programmable hardware components, active storage, flash storage, in-memory cloud systems, and embedded sensors. They address many pursuits of national defense and cybersecurity, weather prediction, health- and disease-monitoring, Industrial IoT, etc. In IUCRC/CARTA Phase II, we will develop new accelerated and real-time approaches to these technologies and their integration relevant to our partners.We will leverage our cutting-edge research in AI/ML and programmable cyber-systems to conduct collaborative CARTA research. Our research areas include accelerated medical image analytics, explainable and interpretable AI/ML for medical and vision/language models, digital twins for dynamical systems with acceleration, and physics-based modeling with AI/ML for improved understanding. Our research will be primarily “application neutral;” i.e., the techniques can be applied with modifications across multiple industry sectors, including cyber security, healthcare and medical, dynamic systems, environment, and business intelligence. Our exploration will include deep learning, semi-supervised learning, federated learning, architectures, image understanding, real-time simulations, and blockchains. Our project will benefit businesses by providing a larger pool of highly skilled workforce. We will disseminate the results of this collaborative research with industry widely by publishing them in appropriate journals and conferences. We will leverage our many programs for our underrepresented students both in the undergraduate and the graduate populations to recruit students for summer internships at our industry partners and to do research in CARTA projects. We will also leverage our MS and PhD in Data Science, Analytics and Engineering programs to find opportunities for the students to do projects as industry interns.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.

加速和实时分析是智能数据革命的前沿，一方面是互联网连接传感器硬件的进步，另一方面是加速的AI/ML分析。这些技术包括机器学习、认知、量子、神经形态和边缘计算，并结合新型传感和可编程硬件组件、主动存储、闪存存储、内存中云系统和嵌入式传感器。在IUCRC/CARTA第二阶段，我们将开发新的加速和实时方法，以实现这些技术及其与合作伙伴相关的集成。我们将利用我们在AI/ML和可编程网络系统方面的前沿研究，开展CARTA合作研究。我们的研究领域包括加速医学图像分析，用于医学和视觉/语言模型的可解释和可解释的AI/ML，用于加速动态系统的数字双胞胎，以及基于物理的AI/ML建模以提高理解。我们的研究将主要是“应用中立”，即，这些技术可以在多个行业部门（包括网络安全、保健和医疗、动态系统、环境和商业智能）中进行修改后应用。我们的探索将包括深度学习，半监督学习，联邦学习，架构，图像理解，实时模拟和区块链。我们的项目将通过提供更大的高技能劳动力库而使企业受益。我们将通过在适当的期刊和会议上发表与工业界广泛传播这项合作研究的结果。我们将利用我们的许多计划，为我们在本科和研究生人口中代表性不足的学生招募学生在我们的行业合作伙伴的暑期实习，并在CARTA项目中进行研究。我们还将利用我们的数据科学，分析和工程硕士和博士课程，为学生寻找机会做项目作为行业实习生。这个奖项反映了NSF的法定使命，并已被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。