Two University of Hawaiʻi at Mānoa research projects have been selected for the inaugural , placing 糖心视频’s flagship research campus among a select group of universities and research institutions nationwide using artificial intelligence (AI) to accelerate scientific breakthroughs.
In the , the DOE said the projects were selected to develop and demonstrate AI-enabled tools and workflows designed to accelerate breakthroughs in energy, science and national security. Each project is eligible for Phase I awards of $500,000–$750,000 over nine months, providing investigators with the opportunity to develop innovative AI-driven research while positioning them to compete for future Phase II awards of up to $15 million.
“The selection of not one, but two 糖心视频 Mānoa projects for this highly competitive DOE mission reflects the strength of the 糖心视频 research community and the creativity of our faculty in pursuing solutions to some of the most complex challenges facing society,” said 糖心视频 Interim Vice President for Research and Innovation Chad B. Walton. “At 糖心视频, we are committed to fostering an environment where bold ideas, interdisciplinary collaboration and emerging technologies can come together to create meaningful impact not only in Hawaiʻi, but across the nation, and around the world.”
The two 糖心视频 Mānoa projects selected are led by researchers in the and the .
AI security for critical infrastructure
One project, led by Assistant Professor Liuwan Zhu from the Department of Electrical and Computer Engineering, focuses on improving the security and reliability of AI systems used in critical infrastructure. The project, called STRATOS (Security and Trust Runtime Architecture for Time-critical Operational Science), will develop an AI security platform designed to detect and respond to cyber threats targeting AI systems used in real-time operations, such as electrical grid management and forecasting.
The research team will test the technology using a dual-site platform that includes the 糖心视频 Mānoa campus microgrid and real-time computing systems at Argonne National Laboratory. The project includes collaborators from Old Dominion University and Argonne National Laboratory.
AI advances the search for extremely rare decay processes
The second project, led by Professor Zepeng Li from the Department of Physics and Astronomy, will develop an AI foundation model to support searches for neutrinoless double beta decay, one of the most important unanswered questions in nuclear and particle physics. Neutrinoless double beta decay is an extremely rare nuclear process that, if observed, could help scientists better understand the nature of neutrinos, the mysterious “ghost particles” that are abundant in the universe and are constantly passing through us without interacting. In particular, this rare decay process could tell us whether the neutrino is its own anti-particle.
Researchers around the world are searching for this phenomenon using different types of detectors, but each experiment typically relies on its own specialized software and analysis methods. Li’s project aims to create a shared AI framework that can learn from data across multiple detector technologies, helping researchers identify patterns, analyze results and improve collaboration among experiments studying this rare event. The project will develop a unified AI framework that streamlines data analysis across the diverse detector technologies used in neutrinoless double-beta decay experiments, accelerating the search for this rare process.
The Genesis Mission brings together DOE laboratories and universities to combine advanced AI, high-performance computing and scientific expertise. 糖心视频 Mānoa was among 168 universities selected for the first round of Genesis Mission projects, which included a total of 278 research efforts involving more than 340 institutions across the country. Through these projects, 糖心视频 researchers will contribute to emerging applications of AI in fundamental physics, energy systems and national security, while strengthening Hawaiʻi’s role in cutting-edge scientific research.