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After successful virtual summer, DSSI looks ahead to 2021
Dec. 14, 2020 -
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...
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...
DOE announces five new energy projects at LLNL
Nov. 13, 2020 -
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...
From intern to mentor, Nisha Mulakken builds a career in bioinformatics
Nov. 3, 2020 -
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 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...
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...
Software integration of AI accelerators in HPC (VIDEO)
July 31, 2020 -
In this episode of Next Platform TV, LLNL's Brian Van Essen talks about AI accelerator integration in HPC systems and software stacks. His interview begins at timestamp 27:57. Watch on YouTube.
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...
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...
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 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.
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.