Data Science in the News

Did you know we have a monthly newsletter? View past volumes and subscribe.

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...

Consulting service infuses Lab projects with data science expertise

June 5, 2023 - 
A key advantage of LLNL’s culture of multidisciplinary teamwork is that domain scientists don’t need to be experts in everything. Physicists, chemists, biologists, materials engineers, climate scientists, computer scientists, and other researchers regularly work alongside specialists in other fields to tackle challenging problems. The rise of Big Data across the Lab has led to a demand for...

Patent applies machine learning to industrial control systems

May 8, 2023 - 
An industrial control system (ICS) is an automated network of devices that make up a complex industrial process. For example, a large-scale electrical grid may contain thousands of instruments, sensors, and controls that transfer and distribute power, along with computing systems that capture data transmitted across these devices. Monitoring the ICS network for new device connections, device...

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...

New HPC4EI project to create 'digital twin' models for aerospace manufacturing

Jan. 19, 2023 - 
A partnership involving LLNL aimed at developing “digital twins” for producing aerospace components is one of six new projects funded under the HPC for Energy Innovation (HPC4EI) initiative, the Department of Energy’s Office of Energy Efficiency and Renewable Energy announced. Sponsored by the HPC4Manufacturing (HPC4Mfg) Program, one of the pillars of HPC4EI, the collaboration between LLNL...

National Ignition Facility achieves fusion ignition

Dec. 13, 2022 - 
The U.S. Department of Energy (DOE) and DOE’s National Nuclear Security Administration (NNSA) today announced the achievement of fusion ignition at LLNL—a major scientific breakthrough decades in the making that will pave the way for advancements in national defense and the future of clean power. On Dec. 5, a team at LLNL’s National Ignition Facility (NIF) conducted the first controlled...

ML model instantly predicts polymer properties

Nov. 30, 2022 - 
Hundreds of millions of tons of polymer materials are produced globally for use in a vast and ever-growing application space with new material demands such as green chemistry polymers, consumer packaging, adhesives, automotive components, fabrics and solar cells. But discovering suitable polymer materials for use in these applications lies in accurately predicting the properties that a...

Understanding the universe with applied statistics (VIDEO)

Nov. 17, 2022 - 
In a new video posted to the Lab’s YouTube channel, statistician Amanda Muyskens describes MuyGPs, her team’s innovative and computationally efficient Gaussian Process hyperparameter estimation method for large data. The method has been applied to space-based image classification and released for open-source use in the Python package MuyGPyS. MuyGPs will help astronomers and astrophysicists...

Papers win Test of Time awards at 2022 IEEE VIS conference

Oct. 31, 2022 - 
Two LLNL-led teams received SciVis Test of Time awards at the 2022 IEEE VIS conference on Oct. 18, for papers that have achieved lasting relevancy in the field of scientific visualization. Published in 2008, an LLNL-led paper that—for the first time—allowed Digital Morse Theory to be applied to large scale and three-dimensional data, won the 14-year Test of Time award for making a lasting...

Project co-led at LLNL looks to improve visualization of largescale datasets

Oct. 27, 2022 - 
LLNL researchers are starting work on a three-year project aimed at improving methods for visual analysis of large heterogeneous data sets as part of a recent Department of Energy funding opportunity. The joint project, entitled “Neural Field Processing for Visual Analysis,” will be led at LLNL by co-principal investigator (PI) Andrew Gillette. Gillette is joined by lead PI Matthew Berger at...

ESGF launches effort to upgrade climate projection data system

Oct. 5, 2022 - 
The Earth System Grid Federation (ESGF), a multi-agency initiative that gathers and distributes data for top-tier projections of the Earth’s climate, is preparing a series of upgrades that will make using the data easier and faster while improving how the information is curated. The federation, led by the Department of Energy’s Oak Ridge National Laboratory in collaboration with Argonne and...

LLNL to cooperate with University of Utah's one oneAPI Center of Excellence

Sept. 21, 2022 - 
The University of Utah has announced the creation of a new oneAPI Center of Excellence focused on developing portable, scalable and performant data compression techniques. The oneAPI Center will be headed out of the University of Utah’s Center for Extreme Data Management Analysis and Visualization (CEDMAV) and will involve the cooperation of LLNL’s Center for Applied Scientific Computing. It...

An open-source, data-science toolkit for energy: GridDS

Aug. 2, 2022 - 
As the number of smart meters and the demand for energy is expected to increase by 50% by 2050, so will the amount of data those smart meters produce. While energy standards have enabled large-scale data collection and storage, maximizing this data to mitigate costs and consumer demand has been an ongoing focus of energy research. An LLNL team has developed GridDS—an open-source, data-science...

Panel discussion spotlights COVID-19 R&D

July 19, 2022 - 
The DSI’s career panel series continued on June 28 to highlight some of LLNL’s COVID-19 research projects. Three data scientists—Emilia Grzesiak, Derek Jones, and Priyadip Ray—joined moderator and data scientist Stewart He to talk about their work in drug screening, protein–drug compounds, antibody–antigen sequence analysis, and risk factor identification. He, who earned a PhD in Computer...

UC Merced students work with LLNL mentors on potential new drugs to combat COVID-19

June 30, 2022 - 
Students from the University of California, Merced worked with mentors at LLNL to identify drug compounds that could be used to treat COVID-19 during a two-week Data Science Challenge (DSC) that concluded on June 6. For the first time in the DSC series since the COVID-19 pandemic began in 2020, Lab mentors visited the college campus to provide in-person guidance for five teams of UC Merced...

LLNL’s Brase discusses advances by ATOM in accelerating drug discovery pipeline

June 7, 2022 - 
The private-public Accelerating Therapeutic Opportunities in Medicine (ATOM) consortium is showing “significant” progress in demonstrating that HPC and M) tools can speed up the drug discovery process, said Jim Brase, ATOM co-lead and LLNL’s deputy associate director for data science. The consortium currently boasts more than a dozen member organizations, including national laboratories...