Ján Drgoňa discussed differentiable programming at the 2024 symposium
PNNL data scientist Ján Drgoňa was selected to speak at the Grainger Foundation Frontiers of Engineering 2024 Symposium of the National Academy of Engineering.
(Photo by Andrea Starr | Pacific Northwest National Laboratory)
Ján Drgoňa, who is a data scientist at Pacific Northwest National Laboratory (PNNL), was featured as a speaker at the Grainger Foundation Frontiers of Engineering (FOE) 2024 Symposium of the National Academy of Engineering (NAE). The event was held on September 11–14 at the National Academies’ Beckman Center in Irvine, California.
The symposium explored the themes of water–air–surface connections for microbiology and health, the future of artificial intelligence (AI), understanding and engineering connections between the gut and the brain, and the digital twin revolution. Drgoňa’s expertise in both AI and digital twins suited the themes well—he is one of the architects of NeuroMANCER, a popular scientific machine learning library he codeveloped with his colleagues at PNNL. His talk at the FOE symposium focused on differentiable programming for data-driven modeling, optimization, and control with applications to building energy systems.
“Ján leads the development of PNNL’s NeuroMANCER open-source framework for solving constrained optimization problems,” said James (Jim) Ang, Chief Scientist for Computing at PNNL. “His work has leveraged institutional laboratory directed research and development support to establish follow-on direct funding.”
“It is a great honor to be selected as one of the 15 speakers at the NAE symposium. This invitation reflects the impact of not only my individual contributions, but our collective team effort at PNNL in developing new tools and methods for modeling and control of energy systems,” said Drgoňa.
PNNL supports a wide variety of AI-related work. The Center for AI @PNNL supports strategic initiatives and shapes the future direction of AI research at the laboratory. PNNL recently announced a partnership with the Department of Energy on the Frontiers in Artificial Intelligence for Science, Security and Technology (FASST) initiative, which will drive advances in AI-ready data, frontier-scale compute, and safe, secure, and trustworthy models, thereby accelerating discovery in science, security, and technology.
Published: October 10, 2024