IUCRC Phase II University of Miami: Center for Accelerated Real Time Analytics (CARTA)

IUCRC 第二阶段迈阿密大学：加速实时分析中心 (CARTA)

• 批准号: 2310807
• 负责人: Mitsunori Ogihara
• 金额: $ 50万
• 依托单位: University of Miami
• 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=2310807&HistoricalAwards=false
• 关键词: IUCRC; Phase; II; University; Miami

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’ll develop new accelerated and real-time approaches to these technologies and their integration relevant to our partners.We’ll 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’ll disseminate the results of this collaborative research with industry widely by publishing them in appropriate journals and conferences and share the results of our research with other non-CARTA institutions that want to duplicate this approach. We’ll 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’ll also leverage our MS in Data Science Program 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，一方面是由互联网连接的传感器硬件的进步推动的，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，结合了新型的感官和可编程硬件组件、主动存储、闪存、内存云系统和嵌入式传感器。它们涉及国防和网络安全、天气预报、健康和疾病监测、工业物联网等诸多领域。在IUCRC/CARTA的第二阶段，我们将开发新的加速和实时的方法来处理这些技术以及与我们的合作伙伴相关的技术整合。我们将利用我们在人工智能/机器学习和可编程网络系统方面的前沿研究来开展合作的CARTA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，用于加速动力系统的数字孪生，以及用于提高理解的基于物理的AI/ML建模。我们的研究将主要是“应用中立”；也就是说，这些技术可以通过修改应用于多个行业部门，包括网络安全、医疗保健、动态系统、环境和商业智能。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。我们的项目将为企业提供更多的高技能劳动力。我们将通过在适当的期刊和会议上发表，广泛传播与工业界合作研究的结果，并与其他希望复制这一方法的非carta机构分享我们的研究结果。我们将利用我们为本科生和研究生群体中代表性不足的学生提供的许多项目，招收学生到我们的行业合作伙伴那里进行暑期实习，并在CARTA项目中进行研究。我们还将利用我们的数据科学硕士项目，为学生寻找作为行业实习生做项目的机会。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。