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Local Women in Data Science conference showcases Lab research
April 3, 2020 -
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
April 3, 2020 -
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...
LLNL creates web resources to aid in fight against COVID-19
March 30, 2020 -
LLNL is fully committed to helping protect the U.S. from COVID-19 and to speed the recovery of those affected. As a world-class research institute, we have considerable infrastructure, unique research capabilities and a dedicated team of scientists and engineers supporting the fight against the COVID-19 pandemic. Our current COVID-19 research and response activities are focused on four broad...
Lab antibody, anti-viral research aids COVID-19 response
March 26, 2020 -
LLNL scientists are contributing to the global fight against COVID-19 by combining artificial intelligence/machine learning, bioinformatics and supercomputing to help discover candidates for new antibodies and pharmaceutical drugs to combat the disease. Armed with the virus’ predicted 3D structure and a few antibodies known to bind and neutralize SARS, an LLNL team led by Daniel Faissol and...
New partnership to unleash U.S. supercomputing resources in the fight against COVID-19
March 26, 2020 -
The White House announced the launch of the COVID-19 High Performance Computing Consortium to provide COVID-19 researchers worldwide with access to the world’s most powerful high performance computing resources that can significantly advance the pace of scientific discovery in the fight to stop the virus. Read more at LLNL News.
DSI sponsors LLNL hackathon
Feb. 18, 2020 -
Since 2012, Lawrence Livermore National Laboratory’s (LLNL’s) Computing directorate has held hackathons three times a year. These spring, summer, and fall events are scheduled over 24 hours and invite software teams to work on new ideas, programming languages, open-source tools, or project tasks. Exploration and experimentation are highly encouraged, and “It’s OK to fail” is the event mantra...
Machine learning accelerates high-performance materials development
Feb. 13, 2020 -
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...
Deep learning may provide solution for efficient charging, driving of autonomous electric vehicles
Feb. 4, 2020 -
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.
Can machine learning improve computer models enough to ignite internal confinement fusion?
Jan. 28, 2020 -
Laser-fusion researchers have turned to machine-learning techniques to seek the combinations of laser pulse characteristics and target design needed to optimize target implosions for inertial confinement fusion. Machine learning has tripled the fusion yield of the simpler direct-drive approach being studied with the OMEGA laser at the University of Rochester. In principle, the Rochester...
LLNL-led team awarded Best Paper at SC19 for modeling cancer-causing protein interactions
Nov. 22, 2019 -
A panel of judges at the International Conference for High Performance Computing, Networking, Storage and Analysis (SC19) on Thursday awarded a multi-institutional team led by Lawrence Livermore National Laboratory computer scientists with the conference’s Best Paper award. The paper, entitled “Massively Parallel Infrastructure for Adaptive Multiscale Simulations: Modeling RAS Initiation...
Department of Energy researchers share data management strategies at first-ever “Data Day”
Nov. 11, 2019 -
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...
Big data illuminates the physical sciences
Nov. 6, 2019 -
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.
Lab leads effort to model proteins tied to cancer
Oct. 31, 2019 -
Computational scientists, biophysicists and statisticians from LLNL and Los Alamos National Laboratory(LANL) are leading a massive multi-institutional collaboration that has developed a machine learning-based simulation for next-generation supercomputers capable of modeling protein interactions and mutations that play a role in many forms of cancer. Read more at LLNL News.
Learning about learning: reading group discusses advancements in AI
Oct. 2, 2019 -
Teams from around Lawrence Livermore conduct research using artificial intelligence, and the Data Science Institute’s (DSI’s) Machine Learning Reading Group serves as a resource for employees to keep one another apprised of developments in this ever-changing field.
The group meets weekly to share and discuss new literature on machine learning and deep learning, subsets of artificial...
Cindy Gonzales forges a new career in data science
Sept. 25, 2019 -
Through LLNL’s Data Science Immersion Program, Gonzales is now among the Lab’s newest data scientists. For two and a half years, she juggled a demanding workload—coordinating Computing’s Scholar Program, interning with data scientists, learning from mentors, supporting LLNL’s Data Science Institute, and attending college part time—while also having her first child. Read more at LLNL Computing...
Collaboration drives data science workshop
Sept. 12, 2019 -
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...
CANDLE illuminates new pathways in fight against cancer
Aug. 16, 2019 -
As part of the Department of Energy’s role in the fight against cancer, scientists are building tools that use supercomputers to solve problems in entirely new ways. Cancer research provides a complex deep learning challenge that enables DOE to develop new supercomputing capabilities that will, in turn, help scientists address challenges in national security and science. The CANcer...
Livermore Lab Foundation awards scholarship to Cal State East Bay computer science student
Aug. 2, 2019 -
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...
Protecting image classification in artificial intelligence
July 8, 2019 -
To address vulnerability concerns in image classification, a new subfield of machine learning has emerged called adversarial machine learning, which focuses on the security of machine learning algorithms. Thomas Hogan, a doctoral student of mathematics at UC Davis, spent his summer investigating this new area of research during the National Science Foundation’s Mathematical Sciences Graduate...
Hyperion Research announces new winners of HPC Innovation Excellence Awards
June 18, 2019 -
Hyperion Research announced the 14th round of recipients of the HPC Innovation Excellence Award at the ISC19 supercomputer industry conference in Frankfurt, Germany. Led by Brian Spears, an LLNL team used the Trinity supercomputer to seek out successful modes of laser-driven fusion implosions by building an enormous database for supervised training of a machine learned surrogate...