Project Grant 2319011
- This $175,000 federal Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) aims to develop new algorithms and computational tools for active sequential change-point detection in high-dimensional streaming data. The research seeks to create effective, scalable methods for quickly identifying anomalies or events in large-scale sensor data, with applications in areas like biosurveillance, environmental monitoring, and homeland...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $100,000 Project Grant to the University of Central Florida (UCF) to develop efficient and effective algorithms for detecting anomalies in high-dimensional spatiotemporal data with large amounts of missing data. Under CFDA 47.049 - Mathematical and Physical Sciences, the project aims to address the challenge of predicting rare anomalies using high-dimensional real-world data with mixed-type multivariate response,...
- The National Science Foundation (NSF) awarded a $100,000 Project Grant under its Mathematical and Physical Sciences program (CFDA 47.049) to the University of Texas at Dallas (UTD) for the project "Predictive Anomaly Detection for Spatio-Temporal Data with Multidimensional Persistence". The project aims to develop novel machine learning and topological data analysis techniques to model spatial and temporal interdependencies in large spatio-temporal datasets, with applications in...
- This National Science Foundation (NSF) Division of Mathematical Sciences Project Grant, under the Mathematical and Physical Sciences program (CFDA 47.049), awarded Colorado State University $144,726 to develop and apply new algebraic tools to enhance statistical and AI methods for detecting outliers, recovering missing data, and identifying hidden constraints in high-dimensional data analysis. The research aims to create a self-adaptive, linear-time algorithm to separate signals, find hidden...
- This National Science Foundation Project Grant of $730,524 will fund the development of new statistical methods for computer-assisted inversion to improve analysis of global remote sensing data from July 2022 to June 2025. Under the Mathematical and Physical Sciences program (CFDA 47.049), Trustees of Boston University will receive funding to advance the transformation of satellite-based remotely sensed data into useful climate and geophysical information. Specifically, the grantee will...
- This $292,362 federal Project Grant award, provided by the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences (CFDA 47.049) program, aims to develop new mathematical theory and statistical tools for monitoring changes in complex systems, such as global trade networks. The project will provide real-time change detection methods with theoretical guarantees for identifying atypical patterns in comprehensive trade databases, with...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $331,902 Project Grant to the Trustees of Boston University on August 15, 2023 under the Mathematical and Physical Sciences program (CFDA 47.049). The purpose of this 3-year grant is to develop rigorous mathematical analysis and theory for the training algorithms used in neural network models across various machine learning applications. The research will leverage stochastic analysis and weak convergence theory...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $100,000 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the Georgia Tech Research Corporation (Georgia Tech) from August 15, 2023 to July 31, 2026. The grant will support the development of a "Novel Distributed, Multi-Channel, Topology-Aware Online Monitoring Framework of Massive Spatiotemporal Data" called A-DMIT. This framework aims to advance online threat detection...
- This Project Grant award from the National Science Foundation (NSF) Division of Mathematical Sciences under the Mathematical and Physical Sciences program (CFDA 47.049) provides $114,416 to Bucknell University to conduct collaborative research on detecting and combating threats embedded within communications streams and online forums. The research aims to develop advanced statistical and artificial intelligence methods to rapidly recover data structures and detect outliers in multidimensional...
- The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $220,000 Project Grant to the International Computer Science Institute (ICSI), a non-profit research organization, under the Mathematical and Physical Sciences program (CFDA 47.049). The project aims to develop resilient and reliable deep learning methods for forecasting complex spatiotemporal ground motion data, with applications in seismology, earth sciences, and other domains. Key technical objectives include...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $249,999 Project Grant to Trustees of Boston University to develop an innovative approach to change-point and anomaly detection using satellite data. The research aims to address challenges in tracking deforestation, degradation, and forest regrowth by leveraging new mathematical frameworks and artificial intelligence techniques. The project will explore applications in areas such as human migration, climate change, transportation, and disease diffusion, while also providing valuable learning opportunities for students. The approach, rooted in functional analysis, offers advantages over current statistical methods, including principled detection of anomalies, development of robust hypothesis tests, and integration of efficient algorithms for processing large data volumes. This grant aligns with the NSF's Mathematical and Physical Sciences program (CFDA 47.049) to advance scientific knowledge and address major national challenges.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $250.0k | 7/19/23 |