Data Science in the News

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DOE honors seven early-career Lab scientists

Sept. 19, 2024 - 
Seven LLNL scientists are recipients of the DOE's Office of Science Early Career Research Program (ECRP) award. Among them is Shusen Liu, a computer scientist in the Machine Intelligence Group in the Center for Applied Scientific Computing. His work focuses on understanding and interpreting the inner mechanisms of neural networks and integrating human domain knowledge with machine...

LLNL researchers unleash machine learning in designing advanced lattice structures

Aug. 22, 2024 - 
Characterized by their intricate patterns and hierarchical designs, lattice structures hold immense potential for revolutionizing industries ranging from aerospace to biomedical engineering, due to their versatility and customizability. However, the complexity of these structures and the vast design space they encompass have posed significant hurdles for engineers and scientists, and...

LLNL, DOD, NNSA dedicate Rapid Response Laboratory and supercomputing system to accelerate biodefense

Aug. 15, 2024 - 
LLNL recently welcomed officials from the Department of Defense (DOD) and National Nuclear Security Administration (NNSA) to dedicate a new supercomputing system and Rapid Response Laboratory (RRL). DOD is working with NNSA to significantly increase the computing capability available to the national biodefense programs. The collaboration has enabled expanding systems of the same architecture...

Evaluating trust and safety of large language models

Aug. 8, 2024 - 
Accepted to the 2024 International Conference on Machine Learning, two Livermore papers examined trustworthiness—how a model uses data and makes decisions—of large language models, or LLMs. In “TrustLLM: Trustworthiness in Large Language Models,” Bhavya Kailkhura and collaborators from universities and research organizations around the world developed a comprehensive trustworthiness...

Probing carbon capture, atom-by-atom

July 31, 2024 - 
A team of scientists at LLNL has developed a machine-learning model to gain an atomic-level understanding of CO2 capture in amine-based sorbents. This innovative approach promises to enhance the efficiency of direct air capture (DAC) technologies, which are crucial for reducing the excessive amounts of CO2 already present in the atmosphere. The low cost of these sorbents has enabled several...

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...

The Laboratory’s habit of innovation

June 4, 2024 - 
LLNL’s HPC and data science capabilities play a significant role in international science research and innovation, and Lab researchers have won 10 R&D 100 Awards in the Software–Services category in the past decade. The latest issue of Science & Technology Review features several award-winning projects, including ZFP and CANDLE: (1) ZFP introduces a new method of compressing large data sets...

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...

GUIDE team develops approach to redesign antibodies against viral pandemics

May 8, 2024 - 
In a groundbreaking development for addressing future viral pandemics, a multi-institutional team involving LLNL researchers has successfully combined an AI-backed platform with supercomputing to redesign and restore the effectiveness of antibodies whose ability to fight viruses has been compromised by viral evolution. The team’s research is published in the journal Nature and showcases a...

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...

Conference paper illuminates neural image compression

Dec. 8, 2023 - 
An enduring question in machine learning (ML) concerns performance: How do we know if a model produces reliable results? The best models have explainable logic and can withstand data perturbations, but performance analysis tools and datasets that will help researchers meaningfully evaluate these models are scarce. A team from LLNL’s Center for Applied Scientific Computing (CASC) is teasing...

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...

Data Days brings DOE labs together for discussions on data management and more

Nov. 9, 2023 - 
Data researchers, developers, data managers, and program managers from the DOE national laboratories visited LLNL on October 24–26 to discuss the latest in data management, sharing, and accessibility at the 2023 DOE Data Days (D3) workshop. Sponsored by the National Nuclear Security Administration’s (NNSA) Office of Defense Nuclear Nonproliferation and hosted annually by LLNL, the event...

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...

Making machine learning safer for biomedicine

Aug. 15, 2023 - 
It’s hard to understate the impact machine learning will have on biomedicine. The ability to train computers to spot patterns by analyzing large, complex datasets is driving discoveries in heart disease, cancer, neurodegenerative diseases and more. For instance, Argonne National Laboratory (ANL) has used machine learning to aid cancer research and accelerate COVID-19 antiviral discovery. One...