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Lab team studies calibrated AI and deep learning models to more reliably diagnose and treat disease
May 29, 2020 -
A team led by LLNL computer scientist Jay Thiagarajan has developed a new approach for improving the reliability of artificial intelligence and deep learning-based models used for critical applications, such as health care. Thiagarajan recently applied the method to study chest X-ray images of patients diagnosed with COVID-19, arising due to the novel SARS-Cov-2 coronavirus. Read more at LLNL...
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.
AI hardware for future HPC systems (VIDEO)
May 20, 2020 -
This interview with Brian Spears, who leads cognitive simulations at LLNL, covers the current state of evaluation of AI chips and how those will mesh with existing and future HPC systems. Watch on YouTube.
COVID-19 research goes public through new portal
May 18, 2020 -
A new online data portal is making available to the public a wealth of data LLNL scientists have gathered from their ongoing COVID-19 molecular design projects, particularly the computer-based “virtual” screening of small molecules and designed antibodies for interactions with the SARS-CoV-2 virus for drug design purposes. The portal houses a wealth of data LLNL scientists have gathered from...
Interpretable AI in healthcare (PODCAST)
May 17, 2020 -
LLNL's Jay Thiagarajan joins the Data Skeptic podcast to discuss his recent paper "Calibrating Healthcare AI: Towards Reliable and Interpretable Deep Predictive Models." The episode runs 35:50. Listen at Data Skeptic.
Faces of STEM: Brenda Ng (VIDEO)
May 11, 2020 -
In this video, LLNL machine learning scientist Brenda Ng explains why she loves her job in STEM, what advice she has for others, what inspired her to go into STEM, and what she does in her free time. Watch on YouTube.
Building knowledge and insights using machine learning of scientific articles
May 5, 2020 -
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...
The incorporation of machine learning into scientific simulations at LLNL (VIDEO)
May 5, 2020 -
In this video from the Stanford HPC Conference, Katie Lewis presents "The Incorporation of Machine Learning into Scientific Simulations at Lawrence Livermore National Laboratory." Read more and watch the video at insideHPC.
New partnership results in increased access to compelling 'real world data'
April 21, 2020 -
Through a new partnership between the UC San Diego Library, Halıcıoğlu Data Science Institute (HDSI), and LLNL's Data Science Institute, UCSD library patrons can now access and analyze two new “real world” data sets from LLNL. The Open Data Initiative collection shares some of LLNL’s challenging and unique data sets, which range in complexity from large-scale, domain-specific simulated data...
Using data to build a secure future (PODCAST)
April 21, 2020 -
On the Hidden in Plain Sight podcast, LLNL director Bill Goldstein explains how the Lab crunches data to shape the future. Listen at Mission.org.
Upgrades for LLNL supercomputer from AMD, Penguin Computing aid COVID-19 research
April 21, 2020 -
Under a new agreement, AMD will supply upgraded graphics accelerators for LLNL’s Corona supercomputing cluster, expected to nearly double the system’s peak compute power. The system will be used by scientists through the public/private COVID-19 HPC Consortium, and by LLNL researchers, who are working on discovering potential antibodies and anti-viral compounds for SARS-CoV-2, the virus that...
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.
‘Yes, you can’: UC Merced students learning, growing at Livermore Lab
Feb. 26, 2020 -
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.
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...
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...