Data Science in the News

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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...

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...

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’s Kailkhura elevated to IEEE senior member

Nov. 8, 2023 - 
IEEE, the world’s largest technical professional organization, has elevated LLNL research staff member Bhavya Kailkhura to the grade of senior member within the organization. IEEE has more than 427,000 members in more than 190 countries, including engineers, scientists and allied professionals in the electrical and computer sciences, engineering and related disciplines. Just 10% of IEEE’s...

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...

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...

Cognitive simulation supercharges scientific research

Jan. 10, 2023 - 
Computer modeling has been essential to scientific research for more than half a century—since the advent of computers sufficiently powerful to handle modeling’s computational load. Models simulate natural phenomena to aid scientists in understanding their underlying principles. Yet, while the most complex models running on supercomputers may contain millions of lines of code and generate...

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...

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...

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...

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 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...

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...

Assured and robust…or bust

June 30, 2022 - 
The consequences of a machine learning (ML) error that presents irrelevant advertisements to a group of social media users may seem relatively minor. However, this opacity, combined with the fact that ML systems are nascent and imperfect, makes trusting their accuracy difficult in mission-critical situations, such as recognizing life-or-death risks to military personnel or advancing materials...

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.”...

Winter hackathon meets WiDS datathon

March 9, 2022 - 
Sponsored by the DSI, LLNL’s winter hackathon took place on February 16–17. Hackathons are 24-hour events that encourage collaborative programming and creative problem solving. In addition to traditional hacking, the hackathon included a special datathon competition in anticipation of the Women in Data Science (WiDS) conference on March 7. Hackathon and datathon participants presented their...