Phase I IUCRC University of Oregon: Center for Big Learning

University Of Oregon Eugene, Eugene OR

Investigators

Abstract

Recent advances in machine learning are ushering in a new era in intelligent computing. The NSF Industry/University Collaborative Research Center for Big Learning (CBL) at the University of Oregon (UO) aims to design novel algorithms and develop efficient systems for deep learning applications in the era of big data. CBL will catalyze diverse expertise of faculty members, students, industry partners, and federal agencies to create state-of-the-art deep learning methodologies, technologies, and applications across broad domains of business, healthcare, and Internet-of-Things. CBL will provide training for new scientists and graduate students, as well as a rich environment for cross-disciplinary engagement. The mission of CBL is to perform pioneering research and development in powerful deep learning algorithms, efficient intelligent systems, and novel applications through unified and coordinated efforts in the CBL consortium. The CBL research team at the UO includes experts in data science, artificial intelligence, machine learning, high-performance computing, health informatics, and bioinformatics. They will explore research projects related to medical record analysis, health behavior prediction, natural language processing, performance optimization, financial forecasting, and computer vision by deploying various deep learning models. CBL is expected to have broad transformative impacts in computational technologies, education, and society. Through research and applications to address a broad spectrum of real-world challenges, CBL will make significant contributions and impacts to the deep learning community. The discoveries from CBL will amplify opportunities for new products and services of industry in general, while delivering key techniques to CBL industry partners in particular. As the nexus of deep learning research and applications, CBL offers an ideal platform to nurture next-generation talents through world-class mentors from both academia and industry, disseminate the cutting-edge technologies, and facilitate industry/university collaborative research. The center's repository is hosted at http://nsfcbl.org. The data, code, and documents will be organized and maintained on the CBL server for the duration of the center plus five years. The internal code repository will be hosted at GitLab. After the software packages are well documented and tested, they will be released and hosted at popular public servers, such as GitHub and Bitbucket.