Excellence in Research: Collaborative Research: Strengthen the Foundation of Big Data Analytics via Interdisciplinary Research among HBCUs

该项目将由来自两个相邻的历史黑人学院和大学（HBCUs），Prairie View A M大学（PVAMU）和德克萨斯南方大学（大津）的跨学科研究团队实施，目标是加强大数据分析的理论基础，并在此基础上开发一种新型的深度学习软件包。围绕大数据的挑战影响了许多领域，并鼓励进行令人兴奋的进一步调查，以了解现实世界应用程序的复杂需求。具体来说，该团队的目标是：1）利用现代物理学的量子理论提高深度神经网络的理解和可解释性; 2）增强深度神经网络的数学基础; 3）利用可扩展的新算法提高深度学习训练过程的计算效率;以及4）将深度学习研究创新实施到新的深度学习软件包中，以部署在云计算和高性能计算平台。该项目将通过提供深度学习模型和改进的计算效率和可扩展性，帮助从学术研究到石油和天然气行业以及军事等广泛应用领域的研究。学生将受益于为科学研究和技术前沿做出贡献的机会。该项目将扩大参与，为代表性不足的少数民族学生的各种群体提供令人振奋的研究机会。两个校区和跨学科团队的成员相辅相成;通过交流和分享专业知识和学生，合作因此在多个层面上产生了有益的协同效应。该奖项反映了NSF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。

This project will be implemented by an interdisciplinary research team from two neighboring historical Black Colleges and Universities (HBCUs), Prairie View A&M University (PVAMU) and Texas Southern University (TSU), with the goals of strengthening the theoretical foundation of big data analytics and developing a novel deep learning software package based on this enhanced foundation. Challenges around big data impacts many areas and encourages exciting further investigation to understand the complex requirements of real-world applications. Specifically, this team aims to 1) improve the understanding and explainability of deep neural networks with the quantum theory of modern physics; 2) enhance the mathematical foundation of deep neural networks; 3) increase the computation efficiency of the deep learning training process with new algorithms that will scale; and 4) implement the deep learning research innovations into a new deep learning software package to deploy in cloud computing and High-Performance Computing platforms.This project will aid the research in a wide range of areas of applications, from academic studies to the oil and gas industry and the military by offering deep learning models and improved computational efficiency and scalability. Students will benefit from the opportunity to contribute to the forefront of science research and technology. The project will broaden participation by opening stimulating research opportunities to a diverse group of underrepresented minority students. The two campuses and the members of the interdisciplinary team complement each other; by exchanging and sharing expertise and students the collaboration therefore has a beneficial and synergistic effect on multiple levels.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.