Data Science in the News

LLNL staff returns to Texas-sized Supercomputing Conference

The 2022 International Conference for High Performance Computing, Networking, Storage, and Analysis (SC22) returned to Dallas as a large contingent of LLNL staff participated in sessions, panels, paper presentations, and workshops centered around HPC. The world’s largest conference of its kind celebrated its highest in-person attendance since the start of the COVID-19 pandemic, with about 11...

Hackathon puts machine learning in the driver’s seat

After 10 years, the “try something new” spirit of LLNL Computing’s seasonal hackathon is alive and well. The fall 2022 event featured an Amazon Web Services (AWS) DeepRacer machine learning (ML) competition, in which participants used a cloud-based racing simulator to train an autonomous race car with reinforcement learning algorithms. Working in teams or individually, drivers trained their...

LLNL celebrates making the impossible possible during 70th anniversary event

On Tuesday, Oct. 11, more than 5,000 LLNL employees gathered to celebrate the Lab’s 70th anniversary. Throughout the first-ever Employee Engagement Day, dozens of the Lab’s facilities and programs opened their doors for employees to get a close-up look at LLNL’s cutting-edge science and technology. It was a celebration of making the impossible possible, bringing a huge number of Lab...

Scientific discovery for stockpile stewardship

Among the significant scientific discoveries that have helped ensure the reliability of the nation’s nuclear stockpile is the advancement of cognitive simulation. In cognitive simulation, researchers are developing AI/ML algorithms and software to retrain part of this model on the experimental data itself. The result is a model that “knows the best of both worlds,” says Brian Spears, a...

S&TR cover story: The ACES in our hand

Uranium enrichment is central to providing fuel to nuclear reactors, even those intended only for power generation. With minor modifications, however, this process can be altered to yield highly enriched uranium for use in nuclear weapons. The world’s need for nuclear fuel coexists with an ever-present danger—that a nonnuclear weapons nation-state possessing enrichment technology could...

Lab directors discuss LLNL’s past, present and future at ‘historic conversation’

On a historic occasion in the Livermore wine country, the nine living LLNL directors gathered on Sept. 8 to mark the Laboratory’s 70th anniversary, share stories and discuss their vision for the Lab in the coming years. Hosted by the nonprofit Livermore Lab Foundation, the panel brought past directors John Foster Jr., John Nuckolls, Bruce Tarter, George Miller, Parney Albright, and Bill...

Celebrating 10 years of hackathons

Hackathons are one of LLNL Computing’s most enduring and beloved traditions. Although some details have changed since the first hackathon, the premise remains the same: Participants have 24 hours to work on any project of their choosing, whether that’s learning a programming language, building a prototype, developing a new skill, or experimenting with a software framework. They are encouraged...

Lab researchers win top award for machine learning-based approach to ICF experiments

The IEEE Nuclear and Plasma Sciences Society (NPSS) announced an LLNL team as the winner of its 2022 Transactions on Plasma Science Best Paper Award for their work applying machine learning to inertial confinement fusion (ICF) experiments. In the paper, lead author Kelli Humbird and co-authors propose a novel technique for calibrating ICF experiments by combining machine learning with...

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

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

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...

Panel discussion spotlights COVID-19 R&D

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...

CASC team wins best paper at visualization symposium

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.”...

HPCIC webinar series to highlight LLNL/Hartree Center industry engagement and joint research

LLNL and the United Kingdom’s Hartree Centre are launching a new webinar series intended to spur collaboration with industry through discussions on computational science, HPC, and data science. The first Hartree–Livermore joint webinar on Computational Science (HLCS) takes place May 24, where speakers from the Hartree Centre will present industrial collaboration efforts and technical work...

Livermore WiDS provides forum for women in data science

LLNL celebrated the 2022 Global Women in Data Science (WiDS) conference on March 7 with its fifth annual regional event, featuring workshops, mentoring sessions and a discussion with LLNL Director Kim Budil, the first woman to hold that role. For the second straight year, the WiDS Livermore event was entirely virtual due to the COVID-19 pandemic. Attendees tuned in to view talks and...

Winter hackathon meets WiDS datathon

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...

WiDS Livermore returns on March 7

We are hosting our 5th WiDS Livermore regional event to encourage our community of women in computing. We will watch the WiDS Stanford Livestream as well as feature Lab-focused technical talks, mentoring breakout sessions, and a career panel. WiDS Livermore is an independent event hosted by LLNL Ambassadors as part of the annual Women in Data Science (WiDS) Worldwide conference organized by...

Career panel spotlights diversity, equity, and inclusion

The DSI’s career panel series continued on November 3 with a session highlighting diversity, equity, and inclusion (DEI) as well as the Lab’s DEI-focused employee resource groups (ERGs). ERGs are sponsored by LLNL’s Office of Strategic Diversity and Inclusion Programs. Moderator Anh Quach, member of the Asian Pacific American Council (APAC), was joined by four panelists: Raul Viera Mercado...

Building confidence in materials modeling using statistics

LLNL statisticians, computational modelers, and materials scientists have been developing a statistical framework for researchers to better assess the relationship between model uncertainties and experimental data. The Livermore-developed statistical framework is intended to assess sources of uncertainty in strength model input, recommend new experiments to reduce those sources of uncertainty...

Inaugural industry forum inspires ML community

LLNL held its first-ever Machine Learning for Industry Forum (ML4I) on August 10–12. Co-hosted by the Lab’s High-Performance Computing Innovation Center (HPCIC) and Data Science Institute (DSI), the virtual event brought together more than 500 enrollees from the Department of Energy (DOE) complex, commercial companies, professional societies, and academia. Industry sponsors included...

Former interns share insights during career panel

The DSI’s new career panel series continued on August 10 with a session featuring former LLNL interns who converted to full-time employment at the Lab. Inspired by the annual Women in Data Science conference, the panel session was open to all LLNL staff and students. Moderator Mary Silva was joined by panelists from the Computing and Engineering Directorates: Brian Bartoldson, Jose Cadena...