
Alkemi
Simulation workflows for Arbitrary Lagrangian–Eulerian (ALE) methods are highly complex and often require a manual tuning process. There is an urgent need to semi-automate this process to reduce…

AIMS
AIMS (Analytics and Informatics Management Systems) develops integrated cyberinfrastructure for big climate data discovery, analytics, simulations, and knowledge innovation.

GOLLNLP
In response to a DOE grid optimization challenge, the LLNL-led gollnlp team is developing the mathematical, computational, and software components needed to solve problems of the real-world power…
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Ramesh Pankajakshan
Computational Scientist Ramesh Pankajakshan came to LLNL in 2016 directly from the University of Tennessee at Chattanooga. But unlike most recent hires from universities, he switched from research…

Gordon Lau
When computer scientist Gordon Lau arrived at Lawrence Livermore more than 20 years ago, he was a contractor assigned to a laser isotope separation project.

Joshua Senecal
The NIF Computing team plays a key role in this smoothly running facility, and computer scientist Joshua Senecal supports multiple operational areas.
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ATOM Consortium welcomes 3 DOE national labs to accelerate drug discovery
The Accelerating Therapeutics for Opportunities in Medicine consortium, of which LLNL is part, announced the U.S. Department of Energy’s Argonne, Brookhaven and Oak Ridge national labs are joining the consortium to further develop ATOM’s AI-driven drug discovery platform.

Research uncovers missing physics in explosive hotspots
Research conducted on the Quartz supercomputer highlights findings made by scientists that reveal a missing aspect of the physics of hotspots in TATB and other explosives.

'Self-trained' deep learning to improve disease diagnosis
LLNL and IBM research on deep learning models to accurately diagnose diseases from x-ray images won the Best Paper award for Computer-Aided Diagnosis at the SPIE Medical Imaging Conference.