Project Grant 2500983
- This federal Project Grant award of $180,000.00 from the National Science Foundation's (NSF) Mathematical and Physical Sciences program (CFDA 47.049) supports research at Michigan State University to improve the robustness and trustworthiness of artificial intelligence (AI) models. The project aims to establish statistical frameworks for adversarial training in neural networks and develop scalable algorithms that leverage dynamic attack strategies and selective sampling to enhance the...
- The National Science Foundation (NSF) awarded a $1,000,000 Project Grant under the Computer and Information Science and Engineering (CFDA 47.070) federal grant program to the Rector & Visitors of the University of Virginia (UVA). This 4-year project, running from September 2025 to August 2029, will develop strategies and methods to ensure the robustness of deep learning models used in healthcare applications. The key goals are to: 1) Create synthetic data-driven robustness audits that can...
- The National Science Foundation (NSF) awarded a $199,792 Computer and Information Science and Engineering (CISE) program grant to the University of Miami to develop novel methodologies for detecting data shifts in artificial intelligence/machine learning-enabled software as a medical device (AI/ML-SAMD) in medical cyber-physical systems. The project aims to create a framework that allows SAMDs to adapt through real-world learning, enhancing their safety and effectiveness in detecting lung cancer...
- This federal Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) provides $439,954 to Michigan State University (MSU) to develop advanced computational models of the heart that leverage machine learning and artificial intelligence. The goal is to create a multiscale modeling framework that can predict structural and functional changes in the heart due to disease conditions like pathological fibrosis. The...
- This $175,000 project grant from the National Science Foundation's Computer and Information Science and Engineering program will fund the development of robust machine learning methods to address data disparities. The University of Michigan will receive funding from March 2022 through February 2024 to create predictive and causal machine learning tools for medical decision making that are reliable despite inaccuracies from underrepresented patient subgroups. Specifically, the university will...
- This $1,200,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports The Johns Hopkins University in transitioning differentially private federated learning (DP-FL) to enable collaborative, intelligent, and fair skin disease diagnostics on medical imaging cyberinfrastructure (MICI). The key outcomes will be to improve the accuracy and fairness of skin disease diagnosis through the adoption of...
- This National Science Foundation (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) award, totaling $299,392, aims to build a collaborative mechanism for academia, industry, and the public sector to co-design research and development (R&D) directions for data systems and artificial intelligence (AI) to address scientific and societal challenges. The project, led by the Regents of the University of Michigan, will bring together data science and...
- The National Science Foundation (NSF) awarded a $499,997 Project Grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to Trustees of Boston University. The grant, titled "CAREER: MAKING DOMAIN-SPECIFIC AI MODELS STEERABLE BY LEVERAGING FOUNDATIONAL MODELS," aims to develop new methods to make AI systems more transparent and adjustable for clinical applications. The project focuses on improving the fairness and reliability of medical AI by...
- This $113,018 Project Grant awarded by the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) Federal Grant Program (CFDA 47.070) supports research at Michigan State University (MSU) to develop robust machine learning methods for imaging applications. The project aims to advance supervised and unsupervised learning approaches that can effectively reconstruct and correct images using limited training data, while being resilient to perturbations such as...
- This $350,000 Project Grant award from the National Science Foundation's (NSF) Computer and Information Science and Engineering (CISE) program (CFDA 47.070) supports the development of advanced, privacy-preserving generative AI models for anonymizing biometric signals. The project aims to create modular and scalable anonymization methods suitable for both clinical and wearable device bio-signals, which can be customized for diverse demographics and health conditions. This will help preserve...
The National Science Foundation (NSF) awarded a $1,000,000 project grant under the Computer and Information Science and Engineering (CISE) Federal Grant Program to Michigan State University. The funding will support a 4-year research project to advance the fundamental understanding and practical implementation of trade-offs among predictive accuracy, robustness across patient populations, and patient privacy in AI-driven healthcare systems, with a focus on diagnosing skin and soft tissue infections. The project aims to develop innovative algorithms and methodologies to effectively integrate heterogeneous, distributed, and self-supervised data sources to achieve optimal performance under these competing objectives. The research outcomes will establish essential performance benchmarks and deliver robust algorithms with strong theoretical guarantees, thereby enabling the development of safer, more reliable, and trustworthy healthcare technologies that can advance national public health and welfare goals.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $1.0m | 7/24/25 |