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2411453

Project Grant

Overview

Grant Description
Frameworks: Deep learning cyber-infrastructure for the exploration of high dimensional multimodal data.

The BISQUE Deep Learning (BDL) Cyberinfrastructure (CI) project is set to transform scientific research across multiple fields, including materials science, environmental science, and bioimaging.

Utilizing cutting-edge deep learning and computer vision techniques, the BDL CI offers a scalable, user-friendly platform for the management and analysis of vast, complex datasets.

This initiative tackles significant challenges such as meticulous data curation, specialized domain expertise, and the need for scalable solutions for high-dimensional data.

By facilitating scientific discovery and innovation, the BDL CI significantly enhances national scientific capabilities.

Furthermore, it supports education and diversity through comprehensive training programs, making advanced analytical tools accessible to a wider research community and thereby promoting the progress of science.

The BDL-CI provides a sophisticated cloud-based service with an intuitive web interface designed for analyzing extensive, unstructured datasets.

It supports advanced functionalities such as spatio-temporal annotations, object detection, segmentation, localization, classification, and tracking, all underpinned by a robust database backend that ensures data integrity and provenance.

The infrastructure is built for scalability and efficiency, supporting dynamic resource allocation, complex workflow orchestration, and high-volume data management.

Core deliverables include a comprehensive software infrastructure tailored for multimodal imaging data, detailed documentation, a suite of deep learning workflows, and an accessible interface for discovering and utilizing data and models.

This project, driven by a multidisciplinary team from UC Santa Barbara, UC Riverside, and the Smithsonian Institution, ensures broad access and long-term sustainability through strategic collaborations and the integration of community feedback into ongoing development.

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.

Subawards are planned for this award.
Funding Goals
THE GOAL OF THIS FUNDING OPPORTUNITY, "CYBERINFRASTRUCTURE FOR SUSTAINED SCIENTIFIC INNOVATION", IS IDENTIFIED IN THE LINK: HTTPS://WWW.NSF.GOV/PUBLICATIONS/PUB_SUMM.JSP?ODS_KEY=NSF22632
Place of Performance
Santa Barbara, California 93106-0001 United States
Geographic Scope
Single Zip Code
Analysis Notes
Amendment Since initial award the total obligations have increased 52% from $2,500,000 to $3,800,000.
Santa Barbara University Of California was awarded Deep Learning Cyberinfrastructure for Multimodal Data Exploration Project Grant 2411453 worth $3,800,000 from the NSF Office of Advanced Cyberinfrastructure in September 2024 with work to be completed primarily in Santa Barbara California United States. The grant has a duration of 5 years and was awarded through assistance program 47.070 Computer and Information Science and Engineering. The Project Grant was awarded through grant opportunity Cyberinfrastructure for Sustained Scientific Innovation.

Status
(Ongoing)

Last Modified 9/18/25

Period of Performance
9/15/24
Start Date
8/31/29
End Date
26.0% Complete

Funding Split
$3.8M
Federal Obligation
$0.0
Non-Federal Obligation
$3.8M
Total Obligated
100.0% Federal Funding
0.0% Non-Federal Funding

Activity Timeline

Interactive chart of timeline of amendments to 2411453

Subgrant Awards

Disclosed subgrants for 2411453

Transaction History

Modifications to 2411453

Additional Detail

Award ID FAIN
2411453
SAI Number
None
Award ID URI
SAI EXEMPT
Awardee Classifications
Public/State Controlled Institution Of Higher Education
Awarding Office
490509 OFC OF ADV CYBERINFRASTRUCTURE
Funding Office
490509 OFC OF ADV CYBERINFRASTRUCTURE
Awardee UEI
G9QBQDH39DF4
Awardee CAGE
4B561
Performance District
CA-24
Senators
Dianne Feinstein
Alejandro Padilla
Modified: 9/18/25