Professor Christine Chiu selected for highly competitive Department of Energy Genesis Mission project - Department of Atmospheric Science | Colorado State University
Professor Christine Chiu selected for highly competitive Department of Energy Genesis Mission project - The Department of Atmospheric Science at Colorado State University is a leading global institution focusing on graduate education, cutting-edge research, and public service.
July 22, 2026Colorado State University researchers on two different projects were awarded prestigious Phase I Genesis Mission awards from the U. S. Department of Energy, announced at theGenesis Mission Summit on July 22 in Washington D. C. CSU researchers will lead a project to develop a first-of-its-kind data-driven AI model to improve understanding of ice-containing clouds and precipitation. CSU expertise will also contribute to a second project focused on optimizing remote power grids. TheGenesis Missionis a historic national initiative led by the U. S. Department of Energy, which is building the world’s most powerful integrated science discovery platform. By uniting government, industry, academia and philanthropy, it is accelerating breakthroughs in energy, scientific discovery and national security through a new platform that combines AI, supercomputing, quantum systems and advanced scientific instruments. “These projects represent the kind of bold, collaborative science needed to accelerate discovery on our most complex challenges,” saidCassandra Moseley, CSU vice president for research. “They bring together CSU’s deep expertise in atmospheric science, power grids, advanced observations and artificial intelligence to create new capabilities that could benefit researchers well beyond this individual effort. ”The goal of the Phase I RFA awards is to identify promising pathways toward transformative scientific capabilities and establish a foundation for future investment and scale. Project teams will design and demonstrate research workflows that integrate AI with scientific investigation, while rigorously evaluating whether those approaches can accelerate discovery, improve predictive capabilities, enhance experimentation or generate new scientific insights. “These awards reflect CSU’s growing leadership at the intersection of artificial intelligence and atmospheric science,” CSU President Amy Parsons said. “Our researchers are using emerging technologies to tackle questions with enormous implications for communities, natural resources and our shared future. We are proud to contribute CSU’s expertise to this ambitious national initiative. ”CSU’s project, “Latent Representation Learning for Understanding Ice Microphysical and Precipitation Processes Constrained by Radar and In Situ Observations,” will be led by principal investigatorChristine Chiu, a professor in CSU’s department of Atmospheric Science,a department leading worldwide in the use of AI for atmospheric research and weather forecasting. Haonan Chen, an associate professor in Electrical and Computer Engineering,will serve as co-principal investigator. Ice-containing clouds play a central role in Earth’s energy balance and water cycle, generating a substantial share of global rain events from frozen precipitation particles that melt before reaching the surface. Yet these clouds remain among the least understood atmospheric systems because ice crystal growth depends on both local conditions and a particle’s growth history – information that observations rarely capture directly. Existing observations also sample only portions of clouds, providing limited connections between cloud processes aloft and the precipitation reaching the surface. The CSU-led team will approach this challenge by starting with surface precipitation and working backward to identify the minimum information needed to constrain precipitation formation. “This project will provide the scientific community with a fundamentally new way to understand how ice-containing clouds produce precipitation,” Chiu said. “By developing a flexible, data-driven foundation model, we aim to help accelerate discovery across atmospheric science and support future research on water resources, weather prediction and energy systems. ”Read more onSOURCE.