Data Science in the News

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Winter hackathon meets WiDS datathon

March 9, 2022 - 
Sponsored by the DSI, LLNL’s winter hackathon took place on February 16–17. Hackathons are 24-hour events that encourage collaborative programming and creative problem solving. In addition to traditional hacking, the hackathon included a special datathon competition in anticipation of the Women in Data Science (WiDS) conference on March 7. Hackathon and datathon participants presented their...

LLNL team models COVID-19 disease progression and identifies risk factors

Feb. 15, 2022 - 
An LLNL team has developed a comprehensive dynamic model of COVID-19 disease progression in hospitalized patients, finding that risk factors for complications from the disease are dependent on the patient’s disease state. Using a machine learning algorithm on a dataset of electronic health records from more than 1,300 hospitalized COVID-19 patients with ProMedica — the largest health care...

WiDS Livermore returns on March 7

Feb. 10, 2022 - 
We are hosting our 5th WiDS Livermore regional event to encourage our community of women in computing. We will watch the WiDS Stanford Livestream as well as feature Lab-focused technical talks, mentoring breakout sessions, and a career panel. WiDS Livermore is an independent event hosted by LLNL Ambassadors as part of the annual Women in Data Science (WiDS) Worldwide conference organized by...

Understanding materials behavior with data science (VIDEO)

Dec. 21, 2021 - 
Computational chemist Rebecca Lindsey, PhD, explains how machine learning and data science techniques are used to develop diagnostic tools for stockpile stewardship, such as models that predict detonator performance. Lindsey also describes how atomistic simulations improve researchers’ understanding of the microscopic phenomena that govern the chemistry in materials under extreme conditions...

Building better materials with data science (VIDEO)

Nov. 11, 2021 - 
Research engineer Brian Giera, PhD, describes how data science techniques help collect and analyze data from advanced manufacturing processes in order to craft meaningful experiments. With examples of automated microencapsulation, 3D nanoprinting, metal additive manufacturing, laser track welding, and digital twins, Giera explains how interdisciplinary teams apply machine learning to remove...

LLNL joins Human Vaccines Project to accelerate vaccine development and understanding of immune response

Oct. 21, 2021 - 
LLNL has joined the international Human Vaccines Project (HVP), bringing Lab expertise and computing resources to the consortium to aid development of a universal coronavirus vaccine and improve understanding of immune response. The HVP is a nonprofit, public-private partnership with a mission to decode the human immune system and accelerate the development of vaccines and immunotherapies...

Tackling the COVID-19 pandemic

Oct. 11, 2021 - 
To help the U.S. fight the COVID-19 pandemic, LLNL did what it does best: quickly bring together interdisciplinary teams and diverse technologies to address urgent national challenges. This effort includes applying advanced high-performance computing resources to biological research and anayzing complicated computer models and enormous datasets. Read more in Science & Technology Review.

Career panel series kicks off with women in Computing leadership roles

July 6, 2021 - 
More than 100 LLNL staff and students gathered virtually for the first session of a new career panel series inspired by the annual WiDS conference and sponsored by the DSI. Panelists discussed how they have shaped their careers at the Lab and in Computing, their journeys into leadership roles, and how they navigate career challenges. Data scientist and panel series organizer Cindy Gonzales...

COVID-19 detection and analysis with Nisha Mulakken (VIDEO)

June 7, 2021 - 
LLNL biostatistician Nisha Mulakken 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 novel species identification for human health, animal health, biodefense, and environmental sampling...

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...

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...

Lab event encourages growth of women in data science

March 17, 2021 - 
Coinciding with International Women’s Day on March 8, LLNL’s 4th Women in Data Science (WiDS) regional event brought women together to discuss successes, opportunities and challenges of being female in a mostly male field. The Lab’s first-ever virtual WiDS gathering attracted dozens of LLNL data scientists as well as some from outside the Lab, and featured speakers, a career panel and...

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...

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.

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.