Data Science in the News

CASC research in machine learning robustness debuts at AAAI conference

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...

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

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

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...

From intern to mentor, Nisha Mulakken builds a career in bioinformatics

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...

Machine learning model may perfect 3D nanoprinting

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...

LLNL papers accepted into prestigious conference

Two papers featuring LLNL scientists were accepted in the 2020 International Conference on Machine Learning (ICML), one of the world’s premier conferences of its kind. Read more at LLNL News.

Lockdown doesn’t hinder annual Data Science Challenge

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...

AI identifies change in microstructure in aging materials

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.

Building knowledge and insights using machine learning of scientific articles

Nanomaterials are widely used at LLNL and in industry for many applications from catalysis to optics to additive manufacturing. The combination of nanomaterials’ shape, size, and composition can impart unique optical, electrical, mechanical, or catalytic properties needed for a specific application. However, synthesizing a specific nanomaterial and scaling up its production is often...

‘Yes, you can’: UC Merced students learning, growing at Livermore Lab

Just 90 miles UC Merced lies one of the epicenters of the future of technology, innovation and national security. The university and lab have teamed up to lay the groundwork for a direct pipeline between the two, opening a door to research collaborations as well as job and internship opportunities for students and alumni. Read more at UC Merced.

Machine learning accelerates high-performance materials development

Lawrence Livermore National Laboratory (LLNL) and its partners rely on timely development and deployment of diverse materials to support a variety of national security missions. However, materials development and deployment can take many years from initial discovery of a new material to deployment at scale. Now, an interdisciplinary team of LLNL researchers from the Physical and Life Sciences...

Big data illuminates the physical sciences

Livermore teams are applying innovative data analysis and interpretation techniques to advance fundamental science research. This article describes projects in astrophysics and materials science. Read more at Science & Technology Review.

Collaboration drives data science workshop

Lawrence Livermore National Laboratory’s (LLNL’s) Data Science Institute (DSI) hosted its second annual workshop on July 23–24, 2019. Co-sponsored by the University of California (UC) system, the event drew more than 200 participants to Garré Winery in Livermore. A common theme ran throughout both days: Collaboration is always welcome. Indeed, feedback from last year’s workshop inspired a...

Livermore Lab Foundation awards scholarship to Cal State East Bay computer science student

Alan Noun, a computer science student at Cal State University East Bay and the recipient of the Livermore Lab Foundation's first full-year scholarship, has started a summer internship at LLNL. In partnership with Cal State University East Bay (CSUEB), the Livermore Lab Foundation (LLF) awarded Noun a one-year stipend to allow him to devote more time to academics by reducing work he needs to...

LLNL Center for Applied Scientific Computing: accelerating scientific discovery (VIDEO)

The Center for Applied Scientific Computing (CASC) serves as LLNL’s window to the broader computer science, computational physics, applied mathematics, and data science research communities. Major thrust areas in CASC research include: (1) Increasing simulation fidelity by integrating multi-physics and multi-scale models, increasing resolution through advanced numerical methods and more...

Researchers explore machine learning to automate sorting of microcapsules in real-time

Micro-Encapsulated CO2 Sorbents (MECS) — tiny, reusable capsules full of a sodium carbonate solution that can absorb carbon dioxide from the air — are a promising technology for capturing carbon from the atmosphere. To create the caviar-like objects, scientists run three fluids through a series of microfluidic components to create drops that turn into capsules when exposed to ultraviolet...

CASC research showcased at major data science venues

Researchers from LLNL’s Center for Applied Scientific Computing (CASC) are among the Lab’s employees making waves in the data science community, with many prominent accolades, publications, and acceptances in 2018. Data science encompasses some of the hottest technology topics—machine learning (ML), “big data” analysis, artificial intelligence, computer vision, and more—and the Center’s...

LLNL explores machine learning to prevent defects in metal 3D-printed parts in real time

LLNL researchers have developed machine learning algorithms capable of processing the data obtained during metal 3D printing in real time and detecting within milliseconds whether a 3D part will be of satisfactory quality. Read more at LLNL News.

Data science workshop embraces multidisciplinary community

Since launching in early 2018, Lawrence Livermore National Laboratory’s (LLNL’s) Data Science Institute (DSI) has hit the ground running with a series of seminars, collaborative sessions, reading groups and other activities for the LLNL data science community. On August 7–8, 2018, the DSI hosted its inaugural offsite workshop, which was co-sponsored by the University of California (UC). More...

New Data Science Institute supports explosive growth of data science

The Data Science Institute (DSI) is a new multidisciplinary entity supporting growth in this field both across Lawrence Livermore National Laboratory (LLNL) programs and among the external data science community. The DSI is designed to facilitate mission-driven data science through a cohesive vision, increased collaboration, and targeted outreach and recruiting. The DSI is led by Michael...