More than a dozen Virginia Tech researchers are connected to three of the first projects selected for the U.S. Department of Energy’s Genesis Mission.
Launched in November, the Genesis Mission is designed to double America’s scientific productivity by bringing together the Department of Energy’s scientific capabilities, advanced artificial intelligence (AI), and high-performance computing with the nation’s leading researchers. On Wednesday, July 22, the first wave of projects aimed to meet that goal were announced.
“The 278 projects selected today represent the very best of our nation’s scientific enterprise,” U.S. Secretary of Energy Chris Wright said in a news release. “The remarkable number of high-quality proposals we received demonstrates that America’s innovation pipeline is strong, and it points to even greater opportunities for future investment and continued expansion of the Genesis Mission portfolio.”
Virginia Tech faculty members spanning multiple colleges and departments are working on the selected projects and leading two of them.
“These awards reflect the strength, creativity, and national relevance of the research being advanced by Virginia Tech faculty and their collaborators,” said Dan Sui, senior vice president for research and innovation. “Virginia Tech researchers are helping lead the next generation of discovery at the intersection of artificial intelligence, advanced computing, and science. These selections underscore both the excellence of our faculty and the power of collaborative, interdisciplinary research to address complex challenges of national importance. As federal research priorities continue to evolve, success will increasingly depend on the ability to combine scientific expertise, innovation, and agility to accelerate discovery and deliver meaningful impact.”
The research teams will immediately begin developing and demonstrating AI-enabled scientific workflows designed to accelerate scientific discovery across the Department of Energy’s mission areas, according to the news release. Awardees will gain access to the Genesis Mission platform, including AI agent frameworks, advanced AI models, and software made available through industry partners and high-performance computing relities
Virginia Tech research will be involved with the following projects:
AI-enabled co-design of fault-tolerant logical interface in quantum LDPC (low-density parity-check) codes
The goal: This project aims to use artificial intelligence to produce more efficient designs for ensuring the accuracy and resiliency of quantum data. Current methods require a vast abundance of resources to maintain a single unit of quantum information and the calculations required to design a new approach would be near impossible by humans alone. By leveraging artificial intelligence, the research team will be able to design a tool that can then be used to confidently expedite the work of the entire research community.
- Charles Cao, principal investigator, assistant professor, Department of Physics
- Arpit Dua, assistant professor, Department of Physics
- Gretchen Matthews, professor, Department of Mathematics
- Edwin Barnes, professor and Roger H. Moore and Mojdeh Khatam-Moore Dean’s Faculty Fellow, Department of Physics
- Giuseppe Cotardo, assistant professor, Department of Physics
- Sophia Economou, professor, Department of Physics
- Xiadoi Wu, University of Maryland
- Yufei Ding, University of California, San Diego
- Kartick Agarwal, Argonne National Laboratory, Lemont, Illinois
- Vincent Su, BlueQubit, Inc., San Francisco, California
- Brad Lackey, Microsoft Corporation, Redmond, Washington
Advancing multimodal and multidimensional AI to discover connections between cloud microphysics and precipitation
The goal: This project aims to enhance precipitation prediction and empower community preparedness by training AI to simultaneously analyze numerical data (temperature and humidity) and visual representations (graphs and radar). Leveraging data from some of the Department of Energy’s Atmospheric Radiation Measurement sites, the AI models will seek to bridge fine-scale weather details with large-scale pattern recognition. Along with better weather predictions, their goals include extracting new understanding of the processes inside clouds, helping identify current models’ weaknesses, and creating new AI methods and models for analysis of complex or large-scale data across science and engineering.
The team:
- Gabriel Isaacman-VanWertz, principal investigator, professor and Anthony and Catherine Moraco Endowed Faculty Fellow, Charles E. Via, Jr. Department of Civil and Environmental Engineering
- Hosein Foroutan, associate professor, Charles E. Via, Jr. Department of Civil and Environmental Engineering
- Craig Ramseyer, associate professor, Department of Geography
- Stephanie Zick, associate professor, Department of Geography
- Hoda Eldardiry, associate professor, Department of Computer Science
- Jiwen Fan, Argonne National Lab, Lemont, Illinois
- Sibren Isaacman, Loyola University Maryland
AI-enabled process optimization for multi-feed rare earth separation
The goal: The project aims to develop and validate an AI-assisted digital twin capable of optimizing complex rare earth solvent extraction circuits under dynamic operating conditions. They will leverage operational data generated at Aclara’s rare earth separation pilot plant at Virginia Techand combine it with advanced process simulation capabilities developed by Argonne National Laboratory. The resulting platform is expected to improve process stability, increase recovery and product purity, reduce operator intervention, and accelerate the scale-up of domestic rare earth separation technologies.
Virginia Tech is a sub-awardee on this project
The team:
- Aaron Noble, professor and head of the Department of Mining and Minerals Engineering, Virginia Tech principal investor
- Sam Evans, senior research associate, Virginia Tech’s co-principal investigator
- Aclara Resources Inc., Vancouver, Canada
- Argonne National Laboratory, Lemont, Illinois
Contact:
Lindsey Haugh
