The Advanced Computing, Mathematics, and Data (ACMD) Division focuses on basic and applied computing research encompassing data and computational engineering, data science, machine intelligence, high-performance computing, and applied mathematics to support R&D efforts spanning across all Pacific Northwest National Laboratory mission areas.
Our scientists and engineers design next-generation algorithms to analyze, model, and visualize complex systems; develop new artificial intelligence (AI) and machine learning (ML) methods and tools; apply co-design principles to optimize the performance and energy efficiency of future heterogeneous and reconfigurable computing systems; develop, deploy, and operate advanced software and data architectures; apply mathematical modeling and simulation to discover new chemicals and materials; and contribute to advance autonomic control for cyber-enabled infrastructures.
A new digital twin platform can help hydropower dam operators by providing accurate and predictive models of physical turbines that improve facilities and enhance reliability.
Samrat (Sam) Chatterjee, a PNNL chief data scientist and team leader with the Data Sciences and Machine Intelligence group, was co-author of a CSET workshop report on agentic artificial intellilligence
In a recent publication in Nature Communications, a team of researchers presents a mathematical theory to address the challenge of barren plateaus in quantum machine learning.
Neeraj Kumar discusses how AI can transform scientific research at the Platform for Advanced Scientific Computing Conference and Trillion Parameter Consortium European Workshop.
Researchers are planning for an electric grid that deploys machine learning to think ahead, plan for the worst, anticipate demand, and meet consumer needs safely and securely.
PNNL played host in mid-May to the Artificial Intelligence for Robust Engineering & Science workshop, an annual event that explores advances in artificial intelligence
Scientists at PNNL harnessing advances in deep learning, deep reinforcement learning and generative AI to change how science is conducted and achieve original scientific results and breakthroughs.
PNNL computing experts Robert Rallo and Court Corley contribute their knowledge to a recent DOE report on applications of AI to energy, materials, and the power grid.
