Data Science in the News

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The data-driven future of extreme physics

May 19, 2021 - 
By applying modern machine learning and data science methods to “extreme” plasma physics, researchers can gain insight into our universe and find clues about creating a limitless amount of energy. In a recent perspective published in Nature, LLNL scientists and international collaborators outline key challenges and future directions in using machine learning and other data-driven techniques...

DSI virtual seminar series debuts on YouTube

May 19, 2021 - 
Since launching in 2018, the DSI has hosted more than three dozen speakers in its seminar series. These events invite researchers from academia, industry, and other institutions to discuss their work for an hour to an LLNL audience. In 2020, the series transitioned to a virtual format, and a video playlist of recently recorded seminars is available on the Livermore Lab Events YouTube channel...

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...

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...

Winter hackathon highlights data science talks and tutorial

March 24, 2021 - 
The Data Science Institute (DSI) sponsored LLNL’s 27th hackathon on February 11–12. Held four times a year, these seasonal events bring the computing community together for a 24-hour period where anything goes: Participants can focus on special projects, learn new programming languages, develop skills, dig into challenging tasks, and more. The winter hackathon was the DSI’s second such...

Ana Kupresanin featured in FOE alumni spotlight

March 10, 2021 - 
LLNL's Ana Kupresanin, deputy director of the Center for Applied Scientific Computing and member of the Data Science Institute council, was recently featured in a Frontiers of Engineering (FOE) alumni spotlight. Kupresanin develops statistical and machine learning models that incorporate real-world variability and probabilistic behavior to quantify uncertainties in engineering and physics...

Lawrence Livermore computer scientist heads award-winning computer vision research

Jan. 8, 2021 - 
The 2021 IEEE Winter Conference on Applications of Computer Vision (WACV 2021) on Wednesday announced that a paper co-authored by LLNL computer scientist Rushil Anirudh received the conference’s Best Paper Honorable Mention award based on its potential impact to the field. The paper, titled "Generative Patch Priors for Practical Compressive Image Recovery,” introduces a new kind of prior—a...

Data Science Institute collaborates with Livermore Lab Foundation and UC Merced to host two year-long fellowships

Dec. 16, 2020 - 
Early this spring, the Livermore Lab Foundation (LLF) in partnership with the UC Merced, awarded two rising seniors, Jose Garcia-Esparza and Teagan Zuniga, two one-year $15,000 fellowships to participate in the Lab’s Data Science Summer Institute (DSSI) and continue a part-time fellowship at the Lab for the remainder of the 2020–21 school year. The fellowships allow deserving students...

After successful virtual summer, DSSI looks ahead to 2021

Dec. 14, 2020 - 
In a year distinguished by the COVID-19 pandemic, LLNL’s Data Science Summer Institute (DSSI) pivoted quickly to an all-virtual program. The 28 students in the class of 2020 worked from their homes and attended online seminars, one-on-one mentoring sessions, team-building games, and other activities. Instead of an in-person poster session, the students participated in a virtual Summer Slam...

DOE announces five new energy projects at LLNL

Nov. 13, 2020 - 
The DOE today announced two rounds of awards for the High Performance Computing for Energy Innovation Program HPC4EI), including five projects at LLNL. HPC4EI connects industry with the computational resources and expertise of the DOE national laboratories to solve challenges in manufacturing, accelerate discovery and adoption of new materials and improve energy efficiency. The awards were...

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...

LLNL to provide supercomputing resources to universities selected by NNSA Advanced Simulation and Computing program

Oct. 2, 2020 - 
LLNL will provide significant computing resources to students and faculty from nine universities that were newly selected for participation in the National Nuclear Security Administration (NNSA)’s Predictive Science Academic Alliance Program (PSAAP). The program is funded by NNSA’s Office of Advanced Simulation and Computing (ASC) program. The primary focus of this third phrase of PSAAP will...

Advancing healthcare with data science (VIDEO)

Aug. 3, 2020 - 
This video provides an overview of projects in which data scientists work with domain scientists to address major challenges in healthcare. To help fight the COVID-19 pandemic, researchers are developing computer models to search for potential antibody and antiviral drug treatments, sharing a data portal with scientists and the general public, and analyzing drug compounds via a novel text...

Software integration of AI accelerators in HPC (VIDEO)

July 31, 2020 - 
In this episode of Next Platform TV, LLNL's Brian Van Essen talks about AI accelerator integration in HPC systems and software stacks. His interview begins at timestamp 27:57. Watch on YouTube.

Machine learning model may perfect 3D nanoprinting

July 29, 2020 - 
Two-photon lithography (TPL)—a widely used 3D nanoprinting technique that uses laser light to create 3D objects—has shown promise in research applications but has yet to achieve widespread industry acceptance due to limitations on large-scale part production and time-intensive setup. LLNL scientists and collaborators turned to machine learning to address two key barriers to industrialization...

Lockdown doesn’t hinder annual Data Science Challenge

June 26, 2020 - 
Due to the COVID-19 pandemic and shelter-in-place restrictions, this year’s Data Science Challenge with the University of California, Merced was an all-virtual offering. The two-week challenge involved 21 UC Merced students who worked from their homes through video conferencing and chat programs to develop machine learning models capable of differentiating potentially explosive materials from...

Modeling neuronal cultures on 'brain-on-a-chip' devices

June 12, 2020 - 
For the past several years, LLNL scientists and engineers have made significant progress in development of a three-dimensional “brain-on-a-chip” device capable of recording neural activity of human brain cell cultures grown outside the body. The team has developed a statistical model for analyzing the structures of neuronal networks that form among brain cells seeded on in vitro brain-on-a...

Carnegie Live: high energy density science and AI (VIDEO)

June 9, 2020 - 
In this Carnegie Live video, Seiichi Shimasaki, Science Counselor for the Japanese embassy in the U.S., described a multiyear science research program (nicknamed the “Moonshot”) to develop new technologies that help solve some of society’s most pressing challenges. He explained that the Government of Japan was looking for a data science program to mentor young scientists, which led to the...

AI identifies change in microstructure in aging materials

May 26, 2020 - 
LLNL scientists have taken a step forward in the design of future materials with improved performance by analyzing its microstructure using AI. The work recently appeared online in the journal Computational Materials Science. Read more at LLNL News.