Data Science in the News

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

Dec. 7, 2020 - 
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...

Model for COVID-19 drug discovery a Gordon Bell finalist

Nov. 17, 2020 - 
A machine learning model developed by a team of LLNL scientists to aid in COVID-19 drug discovery efforts is a finalist for the Gordon Bell Special Prize for High Performance Computing-Based COVID-19 Research. Using Sierra, the world’s third fastest supercomputer, LLNL scientists produced a more accurate and efficient generative model to enable COVID-19 researchers to produce novel compounds...

Machine learning speeds up and enhances physics calculations

Oct. 1, 2020 - 
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...

The internship that launched a machine-learning target revolution

Oct. 1, 2020 - 
Kelli Humbird came to LLNL as a student intern and became a teacher of new data science techniques. In this profile, she describes her experiences and the path that led to her research inertial confinement fusion. Read more at the National Ignition Facility.

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...

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...

DL-based surrogate models outperform simulators and could hasten scientific discoveries

June 17, 2020 - 
Surrogate models supported by neural networks can perform as well, and in some ways better, than computationally expensive simulators and could lead to new insights in complicated physics problems such as inertial confinement fusion (ICF), LLNL scientists reported. Read more at LLNL News.

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...

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.

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...

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 ML platform generates novel COVID-19 antibody sequences for experimental testing

May 1, 2020 - 
LLNL researchers have identified an initial set of therapeutic antibody sequences, designed in a few weeks using machine learning and supercomputing, aimed at binding and neutralizing SARS-CoV-2, the virus that causes COVID-19. The research team is performing experimental testing on the chosen antibody designs. Read more at LLNL News.

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...

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...

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.