NSF invests $3.6M in convergent research to address societal challenges
The U.S. National Science Foundation (NSF) announced three new awards through the NSF Growing Convergence Research (NSF GCR) program, representing an investment of $3.6 million to accelerate innovative, interdisciplinary research addressing complex scientific and societal challenges. These projects will advance cutting‑edge research in robotics, agriculture and flood prediction.
The three newly funded projects are expected to develop new research frameworks, partnerships and tools that strengthen the nation's capacity for convergent science. Each project brings together multi‑institutional teams developing convergent approaches, training the next generation of interdisciplinary researchers and mobilizing knowledge toward impactful outcomes. The research integrates fields such as anthropology, artificial intelligence, data science, engineering, hydrology, microbiology, the physical and biological sciences and the social and behavioral sciences.
"Convergence research is essential for addressing the most pressing challenges facing our communities, our economy and our planet," said Alicia J. Knoedler, head of the NSF Office of Integrative Activities. "These new awards exemplify the creativity and capability of teams working at the intersections of disciplines, and they demonstrate how NSF investments catalyze productive ways of generating knowledge that lead to meaningful, long‑term outcomes."
The NSF GCR program supports teams that intentionally integrate knowledge, methods and expertise across multiple scientific and engineering domains to create new research ecosystems capable of transformative breakthroughs. By fostering shared conceptual frameworks and deep collaboration, the program aims to generate solutions that cannot be achieved within the boundaries of any single discipline.
The awardees and summary of each project are listed below:
- AI-Powered Human-Centric Affordable Assistive Robotics for Mobility and Community
Led by New York University, this project aims to create assistive robotic systems using AI, biosensors and other technologies. The research team will combine advances in robotic exoskeletons for human joints, simulation enabled by AI and other approaches to design lightweight, wearable robotic systems that can be personally controlled. The goal is to expand robotic mobility assistance to a wider population for improved independence. (Collaborator: New Jersey Institute of Technology) - Growing Restorative Agroenergy Landscapes
Led by Michigan State University, this project studies ways to enhance the design of solar energy sites in farming areas. It will gather unique data at solar sites and, through a pioneering research center, analyze how solar structures impact agriculture. Researchers will inspect changes in soil, habitats, water, crops, economy and nearby communities. An advisory group with farmers, local officials and communities will guide the research. Plans include using new data techniques, modeling and community collaboration. Results will guide tools, installations, training and the development of educational workshops and programs. (Collaborators: Dartmouth College, Purdue University, The University of Texas at Dallas) - Predicting Flood-Related Health Threats in At-Risk U.S. Communities
Led by Washington University, this project aims to create a dataset linking flood frequency, pathogen levels in water/soil, resident experiences and infection rates to forecast how flooding impacts infection risk over time/locations. Geospatial analyses will explore the connections between flooding, pathogen levels and risks to human health, using statistical models to enhance the forecasts. An interactive risk map will be created for communities to assess vulnerabilities and strategies to reduce flood impacts. The project includes workshops, citizen science programs and open tools to improve the ability to predict and address flood-related health risks nationwide.