Data Science in the News

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Signal and image science community comes together for annual workshop

June 26, 2024 - 
Nearly 150 members of the signal and image science community recently came together to discuss the latest advances in the field and connect with colleagues, friends, and potential collaborators at the 28th annual Center for Advanced Signal and Image Science (CASIS) workshop. The event featured more than 50 technical contributions across six workshop tracks and a parallel tutorials session...

The surprising places you’ll find machine learning (VIDEO)

June 20, 2024 - 
LLNL data scientists are applying ML to real-world applications on multiple scales. A new DSI-funded video highlights research at the nanoscale (developing better water treatment methods by predicting the behavior of water molecules under the extremely confined conditions of nanotubes); mesoscale (determining the likelihood and location of a dangerous wildfire-causing phenomenon called arcing...

LLNL and BridgeBio announce trials for supercomputing-discovered cancer drug

June 6, 2024 - 
In a substantial milestone for supercomputing-aided drug design, LLNL and BridgeBio Oncology Therapeutics (BridgeBio) today announced clinical trials have begun for a first-in-class medication that targets specific genetic mutations implicated in many types of cancer. The development of the new drug—BBO-8520—is the result of collaboration among LLNL, BridgeBio and the National Cancer...

Statistical framework synchronizes medical study data

June 3, 2024 - 
The risks and benefits of heart surgery, chemotherapy, vaccination, and other medical treatments can change based on the time of day they are administered. These variations arise in part due to changes in gene expression levels throughout the 24-hour day-night cycle, with around 50% of genes displaying oscillatory behavior. To evaluate new therapies, investigators study how a gene’s...

Manufacturing optimized designs for high explosives

May 13, 2024 - 
When materials are subjected to extreme environments, they face the risk of mixing together. This mixing may result in hydrodynamic instabilities, yielding undesirable side effects. Such instabilities present a grand challenge across multiple disciplines, especially in astrophysics, combustion, and shaped charges—a device used to focus the energy of a detonating explosive, thereby creating a...

Accelerating material characterization: Machine learning meets X-ray absorption spectroscopy

May 10, 2024 - 
LLNL scientists have developed a new approach that can rapidly predict the structure and chemical composition of heterogeneous materials. In a new study in ACS Chemistry of Materials, Wonseok Jeong and Tuan Anh Pham developed a new approach that combines machine learning with X-ray absorption spectroscopy (XANES) to elucidate the chemical speciation of amorphous carbon nitrides. The research...

Machine learning tool fills in the blanks for satellite light curves

Feb. 13, 2024 - 
When viewed from Earth, objects in space are seen at a specific brightness, called apparent magnitude. Over time, ground-based telescopes can track a specific object’s change in brightness. This time-dependent magnitude variation is known as an object’s light curve, and can allow astronomers to infer the object’s size, shape, material, location, and more. Monitoring the light curve of...

Will it bend? Reinforcement learning optimizes metamaterials

Dec. 13, 2023 - 
Lawrence Livermore staff scientist Xiaoxing Xia collaborated with the Technical University of Denmark to integrate machine learning (ML) and 3D printing techniques. The effort naturally follows Xia’s PhD work in materials science at the California Institute of Technology, where he investigated electrochemically reconfigurable structures. In a paper published in the Journal of Materials...

Lab partners with new Space Force Lab

Nov. 14, 2023 - 
LLNL subject matter experts have been selected by the U.S. Space Force to help stand up its newest Tools, Applications, and Processing (TAP) laboratory dedicated to advancing military space domain awareness (SDA). The Livermore team attended the October 26 kickoff in Colorado Springs of the SDA TAP lab’s Project Apollo technology accelerator, designed with an open framework to support and...

LLNL, University of California partner for AI-driven additive manufacturing research

Sept. 27, 2023 - 
Grace Gu, a faculty member in mechanical engineering at UC Berkeley, has been selected as the inaugural recipient of the LLNL Early Career UC Faculty Initiative. The initiative is a joint endeavor between LLNL’s Strategic Deterrence Principal Directorate and UC national laboratories at the University of California Office of the President, seeking to foster long-term academic partnerships and...

UC Merced & UC Riverside tackle Data Science Challenge on ML-assisted heart modeling

Aug. 3, 2023 - 
For the first time, students from the University of California (UC) Merced and UC Riverside joined forces for the two-week Data Science Challenge (DSC) at LLNL, tackling a real-world problem in machine learning (ML)-assisted heart modeling. Held in the Livermore Valley Open Campus’s newly remodeled University of California Livermore Collaboration Center from July 10-21, the event brought...

Explainable artificial intelligence can enhance scientific workflows

July 25, 2023 - 
As ML and AI tools become more widespread, a team of researchers in LLNL’s Computing and Physical and Life Sciences directorates are trying to provide a reasonable starting place for scientists who want to apply ML/AI, but don’t have the appropriate background. The team’s work grew out of a Laboratory Directed Research and Development project on feedstock materials optimization, which led to...

Machine learning reveals refreshing understanding of confined water

July 24, 2023 - 
LLNL scientists combined large-scale molecular dynamics simulations with machine learning interatomic potentials derived from first-principles calculations to examine the hydrogen bonding of water confined in carbon nanotubes (CNTs). They found that the narrower the diameter of the CNT, the more the water structure is affected in a highly complex and nonlinear fashion. The research appears on...

High-performance computing, AI and cognitive simulation helped LLNL conquer fusion ignition

June 21, 2023 - 
For hundreds of LLNL scientists on the design, experimental, and modeling and simulation teams behind inertial confinement fusion (ICF) experiments at the National Ignition Facility, the results of the now-famous Dec. 5, 2022, ignition shot didn’t come as a complete surprise. The “crystal ball” that gave them increased pre-shot confidence in a breakthrough involved a combination of detailed...

Visionary report unveils ambitious roadmap to harness the power of AI in scientific discovery

June 12, 2023 - 
A new report, the product of a series of workshops held in 2022 under the guidance of the U.S. Department of Energy’s Office of Science and the National Nuclear Security Administration, lays out a comprehensive vision for the Office of Science and NNSA to expand their work in scientific use of AI by building on existing strengths in world-leading high performance computing systems and data...

Data science meets fusion (VIDEO)

May 30, 2023 - 
LLNL’s historic fusion ignition achievement on December 5, 2022, was the first experiment to ever achieve net energy gain from nuclear fusion. However, the experiment’s result was not actually that surprising. A team leveraging data science techniques developed and used a landmark system for teaching artificial intelligence (AI) to incorporate and better account for different variables and...

LLNL and SambaNova Systems announce additional AI hardware to support Lab’s cognitive simulation efforts

May 23, 2023 - 
LLNL and SambaNova Systems have announced the addition of a spatial data flow accelerator into the Livermore Computing Center, part of an effort to upgrade the Lab’s CogSim program. LLNL will integrate the new hardware to further investigate CogSim approaches combining AI with high-performance computing—and how deep neural network hardware architectures can accelerate traditional physics...

Computing codes, simulations helped make ignition possible

April 6, 2023 - 
Harkening back to the genesis of LLNL’s inertial confinement fusion (ICF) program, codes have played an essential role in simulating the complex physical processes that take place in an ICF target and the facets of each experiment that must be nearly perfect. Many of these processes are too complicated, expensive, or even impossible to predict through experiments alone. With only a few...

Fueling up hydrogen production

April 3, 2023 - 
Through machine learning, an LLNL scientist has a better grasp of understanding materials used to produce hydrogen fuel. The interaction of water with TiO2 (titanium oxide) surfaces is especially important in various scientific fields and applications, from photocatalysis for hydrogen production to photooxidation of organic pollutants to self-cleaning surfaces and biomedical devices. However...

From plasma to digital twins

March 13, 2023 - 
LLNL's Nondestructive Evaluation (NDE) group has an array of techniques at its disposal for inspecting objects’ interiors without disturbing them: computed tomography, optical laser interferometry, and ultrasound, for example, can be used alone or in combination to gauge whether a component’s physical and material properties fall within allowed tolerances. In one project, the team of NDE...