Did you know we have a monthly newsletter? View past volumes and subscribe.
60 years of cancer research
Sept. 10, 2021 -
From studying radioactive isotope effects to better understanding cancer metastasis, the Laboratory’s relationship with cancer research endures some 60 years after it began, with historical precedent underpinning exciting new research areas. In one Cancer Moonshot project, research includes a close synergy between experiments and computation, allowing scientists to get a better picture of the...
LLNL, NNSA and elected officials celebrate opening of Livermore Valley Open Campus expansion
Aug. 26, 2021 -
Leaders from the NNSA, Congressional representatives and local elected officials gathered at LLNL on August 10 to celebrate an expansion to the Livermore Valley Open Campus (LVOC). The Lab hosted a ribbon-cutting ceremony for a new office building (Bldg. 642) and a conference annex (Bldg. 643), which will provide modern office and meeting space for LLNL researchers in predictive biology...
Career panel series kicks off with women in Computing leadership roles
July 6, 2021 -
More than 100 LLNL staff and students gathered virtually for the first session of a new career panel series inspired by the annual WiDS conference and sponsored by the DSI. Panelists discussed how they have shaped their careers at the Lab and in Computing, their journeys into leadership roles, and how they navigate career challenges. Data scientist and panel series organizer Cindy Gonzales...
Brian Gallagher combines science with service
June 20, 2021 -
Brian Gallagher works on applications of machine learning for a variety of science and national security questions. He’s also a group leader, student mentor, and the new director of LLNL’s Data Science Challenge. The Lab has enabled Gallagher to combine scientific pursuits with leadership positions and people-focused responsibilities. “For a long time, my primary motivation was learning new...
Machine learning aids in materials design
June 10, 2021 -
A long-held goal by chemists across many industries is to imagine the chemical structure of a new molecule and be able to predict how it will function for a desired application. In practice, this vision is difficult, often requiring extensive laboratory work to synthesize, isolate, purify, and characterize newly designed molecules to obtain the desired information. Recently, a team of LLNL...
COVID-19 detection and analysis with Nisha Mulakken (VIDEO)
June 7, 2021 -
LLNL biostatistician Nisha Mulakken has enhanced the Lawrence Livermore Microbial Detection Array (LLMDA) system with detection capability for all variants of SARS-CoV-2. The technology detects a broad range of organisms—viruses, bacteria, archaea, protozoa, and fungi—and has demonstrated novel species identification for human health, animal health, biodefense, and environmental sampling...
Lab postdocs invited to prestigious Heidelberg Forum
May 21, 2021 -
Two LLNL postdoctoral researchers are among a select group of 200 scientists invited to attend the 8th Heidelberg Laureate Forum, an international conference that connects young researchers with laureates of the major prizes in mathematics and computer science. For a week in September, LLNL computational engineering postdocs Ruben Glatt and Felipe Leno da Silva will meet and interact with...
Conference papers highlight importance of data security to machine learning
May 12, 2021 -
The 2021 Conference on Computer Vision and Pattern Recognition, the premier conference of its kind, will feature two papers co-authored by an LLNL researcher targeted at improving the understanding of robust machine learning models. Both papers include contributions from LLNL computer scientist Bhavya Kailkhura and examine the importance of data in building models, part of a Lab effort to...
Advanced Data Analytics for Proliferation Detection shares technical advances during two-day meeting
May 7, 2021 -
The Advanced Data Analytics for Proliferation Detection (ADAPD) program held a two-day virtual technical exchange meeting recently. The goal of the meeting was to highlight the science-based and data-driven analysis work conducted by ADAPD to advance the state-of-the-art to accelerate artificial intelligence (AI) innovation and develop AI-enabled systems to enhance the United States’...
A winning strategy for deep neural networks
April 29, 2021 -
LLNL continues to make an impact at top machine learning conferences, even as much of the research staff works remotely during the COVID-19 pandemic. Postdoctoral researcher James Diffenderfer and computer scientist Bhavya Kailkhura, both from LLNL’s Center for Applied Scientific Computing, are co-authors on a paper—“Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural...
Lab offers forum on machine learning for industry
April 22, 2021 -
LLNL is looking for participants and attendees from industry, research institutions and academia for the first-ever Machine Learning for Industry Forum (ML4I), a three-day virtual event starting Aug. 10. The event is sponsored by LLNL’s High Performance Computing Innovation Center and the Data Science Institute. The deadline for submitting presentations or industry use cases is June 30. The...
Virtual seminar series explores data-driven physical simulations
April 6, 2021 -
The rapidly growing fields of artificial intelligence (AI) and machine learning (ML) have become cornerstones of LLNL’s data science research activities. The Lab’s scientific community regularly publishes advancements in both AI/ML applications and theory, contributing to international discourse on the possibilities of these compelling technologies.
The large volume of AI/ML scientific...
ATOM Consortium welcomes 3 DOE national labs to accelerate drug discovery
March 29, 2021 -
The Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium, of which LLNL is part, announced the U.S. Department of Energy’s Argonne, Brookhaven and Oak Ridge national laboratories are joining the consortium to further develop ATOM’s AI-driven drug discovery platform. The public-private ATOM consortium aims to transform drug discovery from a slow, sequential and high-risk...
Lab event encourages growth of women in data science
March 17, 2021 -
Coinciding with International Women’s Day on March 8, LLNL’s 4th Women in Data Science (WiDS) regional event brought women together to discuss successes, opportunities and challenges of being female in a mostly male field. The Lab’s first-ever virtual WiDS gathering attracted dozens of LLNL data scientists as well as some from outside the Lab, and featured speakers, a career panel and...
CASC research in machine learning robustness debuts at AAAI conference
Feb. 10, 2021 -
LLNL’s Center for Applied Scientific Computing (CASC) has steadily grown its reputation in the artificial intelligence (AI)/machine learning (ML) community—a trend continued by three papers accepted at the 35th AAAI Conference on Artificial Intelligence, held virtually on February 2–9, 2021. Computer scientists Jayaraman Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, and Peer-Timo Bremer led...
LLNL physicist wins Young Former Student award
Dec. 16, 2020 -
Texas A&M University’s Department of Nuclear Engineering on December 10 announced it has honored LLNL physicist Kelli Humbird with its 2020-21 Young Former Student award for her work at LLNL in combining machine learning with inertial confinement fusion (ICF) research. Humbird graduated from Texas A&M with a PhD in nuclear engineering in 2019. Since joining the Laboratory as an intern in 2016...
What put LLNL at the center of U.S. supercomputing in 2020?
Nov. 12, 2020 -
The HPC world is waiting for the next series of transitions to far larger machines with exascale capabilities. By this time next year, the bi-annual ranking of the Top500 most powerful systems will be refreshed at the top as Frontier, El Capitan, Aurora, and other DOE systems come online. While LLNL was already planning around AI acceleration for its cognitive simulation aims and had a number...
From intern to mentor, Nisha Mulakken builds a career in bioinformatics
Nov. 3, 2020 -
The COVID-19 pandemic has sparked a wave of new research and development at the Lab, and Nisha Mulakken is very busy. The biostatistician has enhanced the Lawrence Livermore Microbial Detection Array (LLMDA) system with detection capability for all variants of SARS-CoV-2. The technology detects a broad range of organisms—viruses, bacteria, archaea, protozoa, and fungi—and has demonstrated...
AI gets a boost via LLNL, SambaNova collaboration
Oct. 20, 2020 -
LLNL has installed a state-of-the-art artificial intelligence (AI) accelerator from SambaNova Systems, the National Nuclear Security Administration (NNSA) announced today, allowing researchers to more effectively combine AI and machine learning (ML) with complex scientific workloads. LLNL has begun integrating the new AI hardware, SambaNova Systems DataScale™, into the NNSA’s Corona...
LLNL, ANL and GSK provide early glimpse into Cerebras AI system performance
Oct. 13, 2020 -
AI chip and systems startup Cerebras was one of many AI companies showcased at the AI Hardware Summit which concluded last week. Cerebras invited collaborators from LLNL, Argonne National Laboratory, and GlaxoSmithKline to talk about their early work on Cerebras machines and future plans. Livermore Computing's CTO Bronis de Supinski said, “We have this vision for performing cognitive...