The National Science Foundation Division of Mathematical Sciences awarded a $299,999 Project Grant to the Georgia Tech Research Corporation from July 15, 2021 to June 30, 2024 under the Mathematical and Physical Sciences program (CFDA 47.049). The funding will support research investigating the dynamics and kinetics of physical systems. The Mathematical and Physical Sciences program aims to strengthen the Nation's scientific enterprise by promoting progress in mathematical and physical...
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...
The National Science Foundation awarded a $239,999 Project Grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the Georgia Tech Research Corporation from September 15, 2022 to August 31, 2025. The grant funds research to develop mathematical theories and efficient algorithms for multi-marginal optimal transport problems with graphical costs. Specifically, the principal investigator will establish a unified framework for these problems by merging concepts from optimal...
The National Science Foundation (NSF) Division of Mathematical Sciences awarded a $200,000 Project Grant to The University Corporation, a non-profit organization located in Northridge, CA. The grant, funded under the NSF's Mathematical and Physical Sciences program (CFDA 47.049), focuses on developing new statistical modeling and data resampling methods to address challenges posed by incomplete, missing, and fragmented observations in large datasets. Key objectives include: Advancing...
The National Science Foundation Division of Mathematical Sciences awarded a $381,110 project grant to the Georgia Tech Research Corporation to support research titled "CRITICAL AND SUBCRITICAL GROWTH MODELS" under the Mathematical and Physical Sciences program (CFDA 47.049). The three-year award beginning in July 2021 will fund research into critical and subcritical growth models. The Mathematical and Physical Sciences program aims to strengthen the nation's scientific enterprise by...
The National Science Foundation Division of Mathematical Sciences awarded a $198,055 Project Grant to the Georgia Tech Research Corporation from September 1, 2023 through August 31, 2028 under the Mathematical and Physical Sciences federal grant program (CFDA 47.049). The award will support research investigating chaotic dynamics in dynamical systems with noise, and applying tools from smooth ergodic theory and probability theory to rigorously analyze chaotic behavior in practical systems....
The National Science Foundation Directorate for Mathematical and Physical Sciences awarded a $332,336 Project Grant to the Georgia Tech Research Corporation from March 1, 2022 to February 28, 2027. The grant supports research entitled "CAREER: EXPLOITING LOW-DIMENSIONAL STRUCTURES IN DATA SCIENCE: MANIFOLD LEARNING, PARTIAL DIFFERENTIAL EQUATION IDENTIFICATION, AND NEURAL NETWORKS" under the Mathematical and Physical Sciences program (CFDA #47.049). This five-year Project Grant will...
This National Science Foundation (NSF) Mathematical and Physical Sciences (CFDA 47.049) Project Grant award of $200,000 to the Georgia State University Research Foundation Inc. supports research to advance iteratively regularized numerical algorithms for reliable estimation of infectious disease parameters from noisy data. The project aims to develop new regularized alternating minimization algorithms to solve ill-posed parameter-estimation problems constrained by nonlinear dynamics, with...
This Project Grant award from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) provides $175,000 to the University of Georgia Research Foundation, Inc. to initiate a new paradigm for statistical inference of high-dimensional time series data. The project aims to develop self-normalized inference methods that can quantify the accumulative uncertainty of high-dimensional data collected over time, which has been a challenge with existing techniques....
This Project Grant award for $117,910 from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) aims to develop new statistical estimation methods and algorithms that can efficiently process complex, high-dimensional datasets. The research will focus on three key areas: (1) providing rigorous theoretical guarantees for the performance of high-dimensional statistical estimation techniques, (2) establishing computational limits and efficiencies for modern...