On a biannual basis, the Environmental Institute awards grants to UVA faculty in a variety of disciplines that advance solutions to tough environmental challenges. In this cycle, the Institute is pleased to announce five new awards. These projects represent the novel and interdisciplinary approaches required to address some of the most pressing climate crises.
CoLabs
CoLab grants are awarded to novel interdisciplinary pan-University collaborations focused on climate change research with high potential for societal impact. Learn more about CoLab grants here. In this funding cycle, UVA’s Environmental Institute announces the award of the following CoLab grants:
Team: Xi Yang, Sheng Li, Huilin Huang
Description: This project pioneers the integration of very-high-resolution remote sensing and advanced deep learning, a kind of artificial intelligence (AI), to map individual dead trees across the entire Western United States from 2010 to 2025. This innovation addresses a critical gap in wildfire science by capturing tree mortality at unprecedented resolution and scale, reducing one of the largest uncertainties in fire modeling. By bridging AI innovation with ecological modeling, the project enables more precise predictions of fire behavior, strengthens wildfire risk management and resilience strategies of forest managers and the timber industry, and lays the foundation for a better understanding of forest carbon cycling.
Team: Huilin Huang, Hongru Du, Aaron Reuben, Majid Shafiee-Jood
Description: This project introduces a groundbreaking approach to wildfire risk management at the intersection of wildlands and urban areas. Its core innovation is a framework that combines high-resolution physical fire modeling, behavioral decision analysis, and vulnerability assessment, domains that have historically operated in isolation. Advanced fire modeling enables near real-time prediction of fire spread, critical intelligence for emergency planners; connecting this with analysis of evacuation decisions lays the groundwork for AI-driven decision-support tools. A pilot application focused on nursing homes produced tailored evacuation strategies for communities with limited mobility and high vulnerability. By bridging predictive science with actionable planning, this work promises to transform wildfire preparedness, enhance community resilience, and set a new standard for integrated climate-risk management.
Title: Beyond Pattern Recognition: Physics-Informed Embedding Models for Scalable Flood Forecasting
Team: Rich Ngyuen, Stephan De Wekker
Description: This project explores a novel approach to flood forecasting by integrating physics-informed AI with satellite embedding datasets to capture flood vulnerability at the continental scale. The researchers will embed physical conservation laws such as mass, momentum, and energy directly into neural architectures, ensuring predictions are not only efficient but also physically accurate, and advancing the use of AI as a trusted tool for climate adaptation. By deploying physics-informed models through the Floodwatch.io platform, the project will deliver high-resolution flood-risk maps and scalable early warning systems accessible to vulnerable communities lacking advanced infrastructure and improving their preparedness.
Spark grants
Spark grants are awarded to provide seed funding for the creation of interdisciplinary teams that will go on to conduct solutions-focused research on specific environmental issues. Learn more about Spark funding here. In this funding cycle, UVA’s Environmental Institute announces the award of the following Spark grants:
Title: Climate Action for and by the Most Affected: Children Monitoring Air Quality with Wearables
Team: Lucy Bassett, Laura Barnes, Rajesh Balkrishnan, Sarah Sun
Description: This project introduces a novel approach to environmental monitoring by equipping young children in Mexico City with wearable air quality sensors. Unlike traditional stationary monitoring systems, this initiative generates hyperlocal, real-time data tied to children’s daily routines, capturing variations across time, location, and activity level. Working with the community members and policymakers, the research team will make invisible pollution visible, driving evidence-based interventions, and helping communities advocate for climate-smart infrastructure.
Team: Rajesh Balkrishnan, Somayeh Asadi, Kyle Enfield, Josh Colston
Description: This collaboration between the University of Virginia and the Planetary Health Research Centre (PHRC) in Kathmandu addresses severe pollution impacts on population health in Nepal’s Kathmandu Valley. The project introduces tools such as portable lung capacity assessments, GIS-based identification of high-risk areas, and a validated Nepali-language survey instrument to generate data in a region where health impacts of pollution remain under-documented to improve health outcomes.