| NSF Org: |
CNS Division Of Computer and Network Systems |
| Recipient: |
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| Initial Amendment Date: | February 2, 2018 |
| Latest Amendment Date: | August 30, 2022 |
| Award Number: | 1747783 |
| Award Instrument: | Continuing Grant |
| Program Manager: |
Mohan Kumar
mokumar@nsf.gov (703)292-7408 CNS Division Of Computer and Network Systems CSE Directorate for Computer and Information Science and Engineering |
| Start Date: | February 1, 2018 |
| End Date: | January 31, 2025 (Estimated) |
| Total Intended Award Amount: | $750,000.00 |
| Total Awarded Amount to Date: | $1,050,478.00 |
| Funds Obligated to Date: |
FY 2019 = $50,000.00 FY 2020 = $300,478.00 FY 2021 = $350,000.00 |
| History of Investigator: |
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| Recipient Sponsored Research Office: |
1523 UNION RD RM 207 GAINESVILLE FL US 32611-1941 (352)392-3516 |
| Sponsor Congressional District: |
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| Primary Place of Performance: |
1 University of Florida Gainesville FL US 32611-2002 |
| Primary Place of
Performance Congressional District: |
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| Unique Entity Identifier (UEI): |
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| Parent UEI: |
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| NSF Program(s): |
IUCRC-Indust-Univ Coop Res Ctr, Special Projects - CNS |
| Primary Program Source: |
01002223DB NSF RESEARCH & RELATED ACTIVIT 01002021RB NSF RESEARCH & RELATED ACTIVIT 01001920RB NSF RESEARCH & RELATED ACTIVIT 01001819DB NSF RESEARCH & RELATED ACTIVIT 01002021DB NSF RESEARCH & RELATED ACTIVIT 01002122DB NSF RESEARCH & RELATED ACTIVIT 01002122RB NSF RESEARCH & RELATED ACTIVIT |
| Program Reference Code(s): |
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| Program Element Code(s): |
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| Award Agency Code: | 4900 |
| Fund Agency Code: | 4900 |
| Assistance Listing Number(s): | 47.070 |
ABSTRACT
This project establishes the NSF Industry/University Collaborative Research Center for Big Learning (CBL). The vision is to create intelligence towards intelligence-driven society. Through catalyzing the fusion of diverse expertise from the consortium of faculty members, students, industry partners, and federal agencies, CBL seeks to create state-of-the-art deep learning methodologies and technologies and enable intelligent applications, transforming broad domains, such as business, healthcare, Internet-of-Things, and cybersecurity. This timely initiative creates a unique platform for empowering our next-generation talents with cutting-edge technologies of societal relevance and significance.
This project establishes the NSF Industry/University Collaborative Research Center for Big Learning (CBL) at University of Florida (UF). With substantial breakthroughs in multiple modalities of challenges, such as computer vision, speech recognition, and natural language understanding, the renaissance of machine intelligence is dawning. The CBL vision is to create intelligence towards intelligence-driven society. The mission is to pioneer novel deep learning algorithms, systems, and applications through unified and coordinated efforts in the CBL consortium. The UF Site will focus on intelligent platforms and applications and closely collaborate with other sites on deep learning algorithms, systems, and applications.
The CBL will have broad transformative impacts in technologies, education, and society. CBL aims to create pioneering research and applications to address a broad spectrum of real-world challenges, making significant contributions and impacts to the deep learning community. The discoveries from CBL will make significant contributions to promote products and services of industry in general and CBL industry partners in particular. As the magnet 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, disseminates the cutting-edge technologies, and facilitates industry/university collaboration and technology transfer.
The center repository will be hosted at http://nsfcbl.org. The data, code, documents will be well organized and maintained on the CBL servers for the duration of the center for more than five years and beyond. The internal code repository will be managed by GitLab. After the software packages are well documented and tested, they will be released and managed by popular public code hosting services, such as GitHub and Bitbucket.
PUBLICATIONS PRODUCED AS A RESULT OF THIS RESEARCH
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PROJECT OUTCOMES REPORT
Disclaimer
This Project Outcomes Report for the General Public is displayed verbatim as submitted by the Principal Investigator (PI) for this award. Any opinions, findings, and conclusions or recommendations expressed in this Report are those of the PI and do not necessarily reflect the views of the National Science Foundation; NSF has not approved or endorsed its content.
The Center for Big Learning (CBL) explored and pioneered research with industry partners in the frontiers of large-scale deep learning and a broad spectrum of big data applications. The center focused on the design of novel intelligent systems and platforms for deep learning, the transfer of research discoveries to our diverse center members to meet urgent industry needs, and the nurturing of next-generation talents in a mixed academic and industrial setting with real-world relevance and significance via the industry-university consortium. The center consisted of 3 universities (the University of Florida, the University of Oregon, and the University of Missouri-Kansas City) as well as more than 60 professors and 35 companies. Together, this consortium invested in more than 60 projects to support industry-focused research and development.
Projects across the Center's lifetime covered a broad number of applications, including computer vision, natural language processing, data science, bioinformatics, and cyberphysical systems. The projects also advanced our fundamental understanding of deep learning theory, algorithms, and systems. Every project was voted on and selected by industry members of the center to ensure alignment with current needs. In addition, project leaders regularly interacted with industry members to co-design solutions. Results in these projects were published in world-class academic venues.
The Center also focused on workforce development. Trainees at each university regularly interacted with industry members. This provided the trainees with experience on how their research can have a broad practical impact. It also provided industry members with a talent pipeline for new hires. In addition, the Center hosted short courses, seminars, and events to enrich and educate researchers, trainees, and industry members.
Last Modified: 05/09/2025
Modified by: Joel B Harley
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