Data Science in the News

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DSI virtual seminar series debuts on YouTube

May 19, 2021 - 
Since launching in 2018, the DSI has hosted more than three dozen speakers in its seminar series. These events invite researchers from academia, industry, and other institutions to discuss their work for an hour to an LLNL audience. In 2020, the series transitioned to a virtual format, and a video playlist of recently recorded seminars is available on the Livermore Lab Events YouTube channel...

Advanced Data Analytics for Proliferation Detection shares technical advances during two-day meeting

May 7, 2021 - 
The Advanced Data Analytics for Proliferation Detection (ADAPD) program held a two-day virtual technical exchange meeting recently. The goal of the meeting was to highlight the science-based and data-driven analysis work conducted by ADAPD to advance the state-of-the-art to accelerate artificial intelligence (AI) innovation and develop AI-enabled systems to enhance the United States’...

Virtual seminar series explores data-driven physical simulations

April 6, 2021 - 
The rapidly growing fields of artificial intelligence (AI) and machine learning (ML) have become cornerstones of LLNL’s data science research activities. The Lab’s scientific community regularly publishes advancements in both AI/ML applications and theory, contributing to international discourse on the possibilities of these compelling technologies. The large volume of AI/ML scientific...

COVID-19 HPC Consortium reflects on past year

April 1, 2021 - 
COVID-19 HPC Consortium scientists and stakeholders met virtually on March 23 to mark the consortium’s one-year anniversary, discussing the progress of research projects and the need to pursue a broader organization to mobilize supercomputing access for future crises. The White House announced the launch of the public-private consortium, which provides COVID-19 researchers with free access to...

CASC research in machine learning robustness debuts at AAAI conference

Feb. 10, 2021 - 
LLNL’s Center for Applied Scientific Computing (CASC) has steadily grown its reputation in the artificial intelligence (AI)/machine learning (ML) community—a trend continued by three papers accepted at the 35th AAAI Conference on Artificial Intelligence, held virtually on February 2–9, 2021. Computer scientists Jayaraman Thiagarajan, Rushil Anirudh, Bhavya Kailkhura, and Peer-Timo Bremer led...

LLNL physicist wins Young Former Student award

Dec. 16, 2020 - 
Texas A&M University’s Department of Nuclear Engineering on December 10 announced it has honored LLNL physicist Kelli Humbird with its 2020-21 Young Former Student award for her work at LLNL in combining machine learning with inertial confinement fusion (ICF) research. Humbird graduated from Texas A&M with a PhD in nuclear engineering in 2019. Since joining the Laboratory as an intern in 2016...

Data Science Institute collaborates with Livermore Lab Foundation and UC Merced to host two year-long fellowships

Dec. 16, 2020 - 
Early this spring, the Livermore Lab Foundation (LLF) in partnership with the UC Merced, awarded two rising seniors, Jose Garcia-Esparza and Teagan Zuniga, two one-year $15,000 fellowships to participate in the Lab’s Data Science Summer Institute (DSSI) and continue a part-time fellowship at the Lab for the remainder of the 2020–21 school year. The fellowships allow deserving students...

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...

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...

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.

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.

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.

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...

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.