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PROJECTS
Flowchart shows how AMS workflow splits each step into physics code and machine learning models before outputting data

Autonomous MultiScale

AMS is a machine learning solution embedded into scientific applications to automatically replace fine-scale simulations with ancillary models.

zfp velocity field that looks like blue and orange bubbles in varying degrees of granularity

zfp

zfp is an open-source C/C++ library for compressed floating-point and integer arrays that support high throughput read and write random access.

Merlin's logo

Merlin

Merlin is an open-source workflow orchestration and coordination tool that makes it easy to build, run, and process large-scale workflows.

PEOPLE
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Brian Gallagher

Brian Gallagher works on applications of machine learning for a variety of science and national security questions. He’s also a group leader, student mentor, and the new director of LLNL’s Data…

Nisha Mulakken

Nisha Mulakken

Nisha Mulakken is advancing COVID-19 R&D and mentoring the next generation. “The opportunities we are exposed to early in our careers can shape the limits we place on ourselves and our…

Stefanie Guenther

Stefanie Guenther

Lawrence Livermore National Lab has named Stefanie Guenther as Computing’s fourth Sidney Fernbach Postdoctoral Fellow in the Computing Sciences. This highly competitive fellowship is named after…

NEWS
abstract blue and purple background with text overlay "Genesis Mission"

LLNL selected to lead 10 projects under DOE’s Genesis Mission

LLNL scientists and engineers have been selected to lead 10 Phase I projects under the DOE’s Genesis Mission, applying AI to challenges spanning HPC, fusion energy, Earth systems science, materials discovery, biology, quantum technologies, and fundamental physics.

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“AI Science at Scale” summit showcases advances in AI-enabled research and innovation

The summit recognized AI’s growing role in scientific discovery and the Department of Energy’s increasing interest in frontier AI, which subsequently formalized in the Genesis mission.

stock image of three data inputs depicted as groups of strands in blue, pink, and yellow, which start out separately but expand and converge into multicolored ones and zeros

ICML26 acceptances

Don't miss LLNL research accepted to the 43rd International Conference on Machine Learning on July 6–11.