Data Science in the News

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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.

LLNL pairs world’s largest computer chip from Cerebras with Lassen to advance machine learning, AI research

Aug. 19, 2020 - 
LLNL and artificial intelligence (AI) computer company Cerebras Systems have integrated the world’s largest computer chip into the NNSA’) Lassen system, upgrading the top-tier supercomputer with cutting-edge AI technology. Technicians recently completed connecting the Silicon Valley-based company’s massive, 1.2 trillion transistor Wafer-Scale Engine chip—designed specifically for machine...

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.

LLNL papers accepted into prestigious conference

July 9, 2020 - 
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.

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.

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.

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.

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.

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...

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...

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...

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.