Project Grant 2527532
- The National Science Foundation awarded a $160,000 project grant under the Mathematical and Physical Sciences program (CFDA 47.049) to the University of Chicago. The grant, awarded on September 1, 2025, supports collaborative research to develop interpretable machine learning algorithms that can discover mathematical models directly from sparse and noisy ecological data. The goal is to create accurate models to predict how and when insect-killing viruses will protect forests from defoliating...
- This Project Grant award from the National Science Foundation's Mathematical and Physical Sciences program (CFDA 47.049) supports research to accurately quantify recurring seasonal effects in ecological models. The $247,495 award to Texas Tech University System will develop mathematical approaches to represent the complex interactions between short-term and seasonal behaviors in ecosystems, with a focus on assessing the identifiability of model parameters and their ability to match real-world...
- This $300,000 Project Grant from the National Science Foundation's Division of Mathematical Sciences, under the Mathematical and Physical Sciences program (CFDA 47.049), will support the development of next-generation mathematical and algorithmic tools to address two key issues in applying machine learning to statistical modeling of time-evolving complex systems: a shortage of informative training data and the high computational costs of high-dimensional problems. Specifically, the...
- This $649,999 Project Grant award from the National Science Foundation (NSF) under the Technology, Innovation, and Partnerships (CFDA 47.084) program supports Farmsense, Inc., a self-certified small disadvantaged business, in developing novel sensor technologies for precise insect pest monitoring and surveillance in agricultural settings. The project aims to create a system inspired by how bats detect and discriminate between different insects, allowing for tracking of insect pests down to the...
- This Project Grant award of $535,370.00 from the National Science Foundation's (NSF) Biological Sciences program (CFDA 47.074) will support a collaborative research project to study the effects of warming and biotic interactions on aphid populations in a Rocky Mountain ecosystem. The research aims to improve understanding of factors that affect insect herbivore abundance under current and future climate scenarios. Through field experiments, the project will test how interactions between...
- This Project Grant award, valued at $100,000.00 and provided by the National Science Foundation (NSF) Biological Sciences (CFDA 47.074) Federal Grant Program, supports a collaborative research project titled "ACED: Planet-Scale AI for Accelerating Environmental Science - Invasive Species and Beyond." The research aims to develop a novel AI framework that combines multiple data sources, including satellite imagery and other visual data, to automatically discover interpretable scientific...
- This $158,371 Project Grant awarded by the National Science Foundation (NSF) under the Biological Sciences (CFDA 47.074) program will fund collaborative research on the integrated dynamics between plants and aphids mediated by above- and below-ground mutualisms in a rapidly warming Rocky Mountain ecosystem. The research aims to: Integrate the direct effects of temperature on aphid development with indirect effects driven by shifts in above- and below-ground ecological interactions. Assess...
- This National Science Foundation (NSF) Biological Sciences program (CFDA 47.074) Project Grant award of $240,000 provides funding for a postdoctoral research fellowship to study the impacts of climate change on insect phenotypes, populations, and communities. The research aims to: 1) build a model to estimate how insect traits like body size and developmental timing respond to temperature variation, 2) quantify how these phenotypic changes affect population dynamics, and 3) determine how...
- This $422,183 Project Grant awarded by the National Science Foundation's Biological Sciences program (CFDA 47.074) will fund research by Southern Oregon University to investigate how temperature and nutrition jointly affect the migratory grasshopper, a major rangeland pest in the United States. The project will combine fieldwork, lab experiments, and computer simulations to improve ecological forecasting and inform pest management strategies to support national food security. The research will...
- 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...
This Project Grant award from the National Science Foundation (NSF) under the Mathematical and Physical Sciences program (CFDA 47.049) aims to advance weak form scientific machine learning (WSCIML) methods and apply them to modeling the dynamics of insect pests and their viral pathogens in forest ecosystems. The $240,000 award to the University of Colorado will fund collaborative research to develop interpretable machine learning algorithms that can generate accurate predictive models directly from sparse and noisy ecological data. The goal is to create robust, evidence-based models to guide the management of insect pests, such as the Douglas-fir tussock moth and spongy moth, which cause millions in forest damage annually. The project will provide research experiences for graduate and undergraduate students and engage high school and university communities through outreach activities.
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $240.0k | 8/14/25 |