Data Science in the News

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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...

For better CT images, new deep learning tool helps fill in the blanks

Nov. 17, 2023 - 
At a hospital, an airport, or even an assembly line, computed tomography (CT) allows us to investigate the otherwise inaccessible interiors of objects without laying a finger on them. To perform CT, x-rays first shine through an object, interacting with the different materials and structures inside. Then, the x-rays emerge on the other side, casting a projection of their interactions onto a...

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...

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...

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...

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...

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...

Scientists develop model for more efficient simulations of protein interactions linked to cancer

March 28, 2023 - 
LLNL scientists have developed a theoretical model for more efficient molecular-level simulations of cell membranes and their lipid-protein interactions, part of a multi-institutional effort to better understand the behavior of cancer-causing membrane proteins. Developed under an ongoing collaboration by the Department of Energy and the National Cancer Institute (NCI) aimed at modeling cell...

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...

Skywing: Open-source software aids collaborative autonomy applications

Jan. 25, 2023 - 
A new software developed at LLNL, and known as Skywing, provides domain scientists working to protect the nation’s critical infrastructure with a high-reliability, real-time software platform for collaborative autonomy applications. The U.S. modern critical infrastructure—from the electrical grid that sends power to homes to the pipelines that deliver water and natural gas and the railways...

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...

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...

LLNL researchers win HPCwire award for applying cognitive simulation to ICF

Nov. 17, 2022 - 
The high performance computing publication HPCwire announced LLNL as the winner of its Editor’s Choice award for Best Use of HPC in Energy for applying cognitive simulation (CogSim) methods to inertial confinement fusion (ICF) research. The award was presented at the largest supercomputing conference in the world: the 2022 International Conference for High Performance Computing, Networking...

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...

LLNL team claims top AI award at international symbolic regression competition

Aug. 16, 2022 - 
An LLNL team claimed a top prize at an inaugural international symbolic regression competition for an artificial intelligence (AI) framework they developed capable of explaining and interpreting real-life COVID-19 data. Hosted by the open source SRBench project at the 2022 Genetic and Evolutionary Computation Conference (GECCO), the competition had two tracks—synthetic and real-world—and...

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...

Defending U.S. critical infrastructure from nation-state cyberattacks

July 21, 2022 - 
For many years, LLNL has been conducting research on cybersecurity, as well as defending its systems and networks from cyberattacks. The Lab has developed an array of capabilities to detect and defend against cyberintruders targeting IT networks and worked with government agencies and private-sector partners to share its cybersecurity knowledge to the wider cyberdefense community. LLNL has...

Introduction to deep learning for image classification workshop (VIDEO)

July 6, 2022 - 
In addition to its annual conference held every March, the global Women in Data Science (WiDS) organization hosts workshops and other activities year-round to inspire and educate data scientists worldwide, regardless of gender, and to support women in the field. On June 29, LLNL’s Cindy Gonzales led a WiDS Workshop titled “Introduction to Deep Learning for Image Classification.” The abstract...

CASC team wins best paper at visualization symposium

May 25, 2022 - 
A research team from LLNL’s Center for Applied Scientific Computing won Best Paper at the 15th IEEE Pacific Visualization Symposium (PacificVis), which was held virtually on April 11–14. Computer scientists Harsh Bhatia, Peer-Timo Bremer, and Peter Lindstrom collaborated with University of Utah colleagues Duong Hoang, Nate Morrical, and Valerio Pascucci on “AMM: Adaptive Multilinear Meshes.”...