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...

LLNL physicist wins Young Former Student award

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...

NeurIPS papers aim to improve understanding and robustness of machine learning algorithms

The 34th Conference on Neural Information Processing Systems (NeurIPS) is featuring two papers advancing the reliability of deep learning for mission-critical applications at LLNL. The most prestigious machine learning conference in the world, NeurIPS began virtually on Dec. 6. The first paper describes a framework for understanding the effect of properties of training data on the...

DOE announces five new energy projects at LLNL

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...

Machine learning speeds up and enhances physics calculations

Interpreting data from NIF’s cutting-edge high energy density science experiments relies on physics calculations that are so complex they can challenge LLNL supercomputers, which stand among the best in the world. A collaboration between LLNL and French researchers found a novel way to incorporate machine learning and neural networks to significantly speed up inertial confinement fusion...

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.

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.

Local Women in Data Science conference showcases Lab research

For the third consecutive year, LLNL hosted a Women in Data Science (WiDS) regional event on March 2. The event drew dozens of attendees from LLNL, Sandia National Laboratories, local universities, and Bay Area commercial companies. Livermore was one of over 200 regional events in 60 countries coordinated with the main WiDS conference at Stanford University. According to the WiDS website...

Lab promotes diversity, tech at Women in Data Science regional event

For the third consecutive year, Lawrence Livermore National Laboratory (LLNL) hosted a Women in Data Science (WiDS) regional event on March 2. Held at the HPC Innovation Center, the event drew dozens of attendees from LLNL, Sandia National Laboratories, local universities, and Bay Area commercial companies. Livermore was one of over 200 regional events in 60 countries coordinated with the...

Deep learning may provide solution for efficient charging, driving of autonomous electric vehicles

LLNL computer scientists and software engineers have developed a deep learning-based strategy to maximize electric vehicle (EV) ride-sharing services while reducing carbon emissions and the impact to the electrical grid, emphasizing autonomous EVs capable of offering 24-hour service. Read more at LLNL News.

Department of Energy researchers share data management strategies at first-ever “Data Day”

It’s become something of a mantra of the digital age: Data is the new currency. Especially in science, where it’s hard to find a single project that doesn’t involve generating or consuming massive amounts of data. In light of the growing awareness of the critical importance of data management across the Department of Energy complex, more than 100 researchers from DOE national laboratories...

Successful simulation and visualization coupling proves the power of Sierra

As the first National Nuclear Security Administration (NNSA) production supercomputer backed by GPU- (graphics processing unit) accelerated architecture, Sierra’s acquisition required a fundamental shift in how scientists at Lawrence Livermore National Laboratory (LLNL) program their codes to take advantage of the GPUs. The majority of Sierra’s computational power—95 percent of its 125...

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...

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...

Making connections, career development highlight Women in Data Science regional event

For the second straight year, the HPC Innovation Center at LLNL played host to a Women in Data Science WiDS) regional event on March 4, drawing in dozens of attendees from LLNL, local universities and other Bay Area national laboratories. Livermore was one of more than 150 regional events held at sites across the globe in conjunction with the Global WiDS conference at Stanford University. Rea...

Going deep: Lab employees get an introduction to world of machine learning, neural networks

Deep learning is one of the most popular and widely used machine learning methods due to its success with autonomous vehicles, speech recognition and image classification, to name a few emergent technologies. But what exactly is deep learning, and how can it best be applied to Lab projects? LLNL employees discovered the answers during a recent "Deep Learning 101" course, which introduced the...

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.

Researchers developing deep learning system to advance nuclear nonproliferation analysis

Artificial neural networks are all around us, deeply embedded in routine functions on the internet. They help online merchants make personalized shopping recommendations, enable social media sites to recognize faces in photos and assist email programs in filtering out spam. Neural networks also have the potential to play a critical role in national security, helping nonproliferation analysts...

Lawrence Livermore scientists link up with Global Women in Data Science conference

LLNL's High Performance Computing Innovation Center hosted a regional event on March 5 tied in with Stanford University’s annual Women in Data Science (WiDS) conference. Nearly 70 attendees, mostly women Livermore and Sandia national laboratory employees, heard featured talks by female LLNL scientists on machine learning and data analytics, and viewed a live broadcast of the daylong world...