NOVEMBER 17, 2023 Article Optimizing Computer Communications Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications. ( Read More )
OCTOBER 30, 2023 Staff Accomplishment Tumeo Takes Computational Chemistry to the Extremes Tumeo will lead the ChemComp project, which was awarded for Exploratory Research in Extreme Scale Science ( Read More )
SEPTEMBER 15, 2023 Staff Accomplishment Stinis to Lead Two New Scientific Machine Learning Projects Stinis will serve as a principal investigator on two of the four projects selected for funding by the Advanced Scientific Computing Research program. ( Read More )
SEPTEMBER 15, 2023 Article Innovative Idea Streamlines Project Planning Researchers unveil user-friendly software to keep complex projects on budget and on schedule. ( Read More )
AUGUST 8, 2023 Staff Accomplishment Świrydowicz Receives Best Paper Award The award was given at the 29th International Conference on Information, Communication and Automation Technologies. ( Read More )
AUGUST 3, 2023 Staff Accomplishment Xu Joins the Editorial Board of Scientific Reports Zhijie (Jay) Xu will apply his expertise in multiscale modeling to this editorial role. ( Read More )
AUGUST 2, 2023 Article Synergizing Techniques to Advance AI PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning. ( Read More )
JULY 31, 2023 Staff Accomplishment Delivering Mighty Impact for DOE User Facility ACMD staff contributed to 30 years of atmospheric data collection for the Department of Energy’s Atmospheric Radiation Measurement user facility. ( Read More )
JUNE 6, 2023 Article Facing Scientific Challenges? We’re Counting on It! PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics. ( Read More )
JUNE 6, 2023 Staff Accomplishment Attarian Leads National Panel at GEOINT Conference Adam Attarian led a new panel session, titled National Labs and the GEOINT Mission, at the GEOINT 2023 Symposium, held May 21–24, 2023. ( Read More )
MAY 16, 2023 Article Try This to Integrate Your Multi-Omics Data with Missing Values Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches. ( Read More )
OCTOBER 31, 2022 Article Simulating the Effects of Climate Change PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change. ( Read More )
OCTOBER 20, 2022 Article Watching the Cold War’s Environmental Footprint Shrink A new web-based tool provides easy-to-understand progress metrics and other data about groundwater cleanup sites overseen by the DOE Office of Environmental Management. ( Read More )
OCTOBER 10, 2022 Staff Accomplishment Charles Joins International Editorial Board for One Health Research and Resources Lauren Charles joins the CABI One Health Editorial Board as an associate editor. ( Read More )
OCTOBER 3, 2022 Article SEA-CROGS Selected for DOE Support SEA-CROGS is one of four Mathematical Multifaceted Integrated Capability Centers selected for support by the Department of Energy. ( Read More )
SEPTEMBER 22, 2022 Article Understanding the Ways of Water New research makes molecular-level calculations of water faster and easier. ( Read More )
AUGUST 17, 2022 Staff Accomplishment PNNL Researchers Lead High Performance Computing Workshop James Ang, John Feo, and Marco Minutoli organized a high performance computing workshop at the prestigious ISC High Performance 2022 conference. ( Read More )
AUGUST 11, 2022 Article Accelerating Machine Learning Through Collaboration PNNL researchers teamed up with SambaNova to enhance artificial intelligence for scientific computing. ( Read More )
JULY 20, 2022 Staff Accomplishment Inspiring Early Career Researchers Through BIG Careers Business, industry, and government careers were a focus of the PNNL-led Mathematics Research Communities conference. ( Read More )
MAY 16, 2022 Staff Accomplishment Decoding Protein Interactions with Domain-Aware Machine Learning Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery. ( Read More )
