Johns Hopkins is part of the new multi-institution Learning Accelerated Domain Sciences (LEADS) Institute, a Department of Energy-funded collaborative initiative focused on reshaping how artificial intelligence supports scientific discovery. Supported through the Scientific Discovery through Advanced Computing (SciDAC) program, the effort seeks to build new AI methods and software tools aimed at solving some of the nation’s most pressing scientific and engineering challenges, including those related to sustainable energy, infrastructure, and materials science.
The Pacific Northwest National Laboratory is leading the effort, which brings together 14 partners, including nine universities and five national laboratories, and will feature scientists across multiple disciplines, ranging from energy systems to materials and computational chemistry. The five-year program includes funding support for three Hopkins principal investigators.
“This isn’t about solving one isolated problem. We’re creating new algorithms and software tools that can address a wide host of challenges,” says Ján Drgoňa, associate professor of civil and systems engineering and a core researcher in the Ralph O’Connor Sustainable Institute (R0SEI). “This work builds upon Hopkins’ leadership at the touchpoint of AI and sustainable energy.”
Along with Drgoňa, the Department of Electrical and Computer Engineering’s Enrique Mallada, an associate professor and associate researcher with ROSEI, and Mahyar Fazlyab, an assistant professor, will lead the Control of Physical Systems efforts, which explores how data-driven AI models and physics-based models can be combined to optimize complex systems.