Data Science in the News

NNSA and Cornelis Networks to collaborate on next-generation high-performance networking

May 4, 2022- 
The Next-Generation High Performance Computing Network (NG-HPCN) project for the NNSA’s Advanced Simulation and Computing (ASC) program will enable NNSA to co-design and partner with Cornelis on development and productization of next-generation interconnect technologies for HPC. The project is led by LLNL for the NNSA Tri-Labs: LLNL, Los Alamos and Sandia national laboratories. The resulting...

Accelerating the path to precision medicine

March 22, 2022- 
LLNL joined the Transforming Research and Clinical Knowledge in Traumatic Brain Injury (TRACK-TBI) consortium in 2018. The national, multiyear, multidisciplinary effort, led by the University of California at San Francisco in collaboration with Lawrence Berkeley and Argonne national laboratories and other leading research organizations and universities, combines neuroimaging, blood-based...

Machine learning model finds COVID-19 risks for cancer patients

March 10, 2022- 
A new study by researchers at LLNL and the University of California, San Francisco, looks to identify cancer-related risks for poor outcomes from COVID-19. Analyzing one of the largest databases of patients with cancer and COVID-19, the team found previously unreported links between a rare type of cancer—as well as two cancer treatment-related drugs—and an increased risk of hospitalization...

COVID-19 R&D: Computing responds to pandemic

Jan. 19, 2022- 
When the COVID-19 pandemic began, the Laboratory immediately started seeking solutions to the myriad challenges posed by the global crisis. The Computing Directorate jumped right in with research and development activities that combine molecular screening to inform antiviral drug experimentation; a generative molecular design software platform to optimize properties of antiviral drugs; an...

LLNL establishes AI Innovation Incubator to advance artificial intelligence for applied science

Dec. 20, 2021- 
LLNL has established the AI Innovation Incubator (AI3), a collaborative hub aimed at uniting experts in artificial intelligence (AI) from LLNL, industry and academia to advance AI for large-scale scientific and commercial applications. LLNL has entered into a new memoranda of understanding with Google, IBM and NVIDIA, with plans to use the incubator to facilitate discussions and form future...

Digital twins for cancer patients could be ‘paradigm shift’ for predictive oncology

Dec. 16, 2021- 
A multi-institutional team, including an LLNL contributor, has proposed a framework for digital twin models of cancer patients that researchers say would create a “paradigm shift” for predictive oncology. Published online Nature Medicine on November 25, the proposed framework for Cancer Patient Digital Twins (CPDTs) — virtual representations of cancer patients using real-time data — would...

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...

Data Science Challenge welcomes UC Riverside

Oct. 11, 2021- 
Together with LLNL’s Center for Applied Scientific Computing (CASC), the DSI welcomed a new academic partner to the 2021 Data Science Challenge (DSC) internship program: the University of California (UC) Riverside campus. The intensive program has run for three years with UC Merced, and it tasks undergraduate and graduate students with addressing a real-world scientific problem using data...

Lab-led effort one of nine DOE-funded data reduction projects

Sept. 17, 2021- 
An LLNL-led effort in data compression was one of nine projects recently funded by the DOE for research aimed at shrinking the amount of data needed to advance scientific discovery. Under the project—ComPRESS: Compression and Progressive Retrieval for Exascale Simulations and Sensors—LLNL scientists will seek better understanding of data-compression errors, develop models to increase trust in...

Inaugural industry forum inspires ML community

Sept. 16, 2021- 
LLNL held its first-ever Machine Learning for Industry Forum (ML4I) on August 10–12. Co-hosted by the Lab’s High-Performance Computing Innovation Center (HPCIC) and Data Science Institute (DSI), the virtual event brought together more than 500 enrollees from the Department of Energy (DOE) complex, commercial companies, professional societies, and academia. Industry sponsors included...

Former interns share insights during career panel

Aug. 19, 2021- 
The DSI’s new career panel series continued on August 10 with a session featuring former LLNL interns who converted to full-time employment at the Lab. Inspired by the annual Women in Data Science conference, the panel session was open to all LLNL staff and students. Moderator Mary Silva was joined by panelists from the Computing and Engineering Directorates: Brian Bartoldson, Jose Cadena...

Virtual LLNL-UC Merced Data Science Challenge tackles asteroid detection though machine learning

June 25, 2021- 
Over three weeks, students from the University of California, Merced collaborated online with mentors at LLNL to tackle a real-world challenge problem: using machine learning to identify potentially hazardous asteroids that could pose an existential threat to humanity. Throughout the event, the teams tackled problems around the theme of “Astronomy for Planetary Defense.” For the main...

Lab postdocs invited to prestigious Heidelberg Forum

May 21, 2021- 
Two LLNL postdoctoral researchers are among a select group of 200 scientists invited to attend the 8th Heidelberg Laureate Forum, an international conference that connects young researchers with laureates of the major prizes in mathematics and computer science. For a week in September, LLNL computational engineering postdocs Ruben Glatt and Felipe Leno da Silva will meet and interact with...

Conference papers highlight importance of data security to machine learning

May 12, 2021- 
The 2021 Conference on Computer Vision and Pattern Recognition, the premier conference of its kind, will feature two papers co-authored by an LLNL researcher targeted at improving the understanding of robust machine learning models. Both papers include contributions from LLNL computer scientist Bhavya Kailkhura and examine the importance of data in building models, part of a Lab effort to...

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’...

A winning strategy for deep neural networks

April 29, 2021- 
LLNL continues to make an impact at top machine learning conferences, even as much of the research staff works remotely during the COVID-19 pandemic. Postdoctoral researcher James Diffenderfer and computer scientist Bhavya Kailkhura, both from LLNL’s Center for Applied Scientific Computing, are co-authors on a paper—“Multi-Prize Lottery Ticket Hypothesis: Finding Accurate Binary Neural...

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...

ATOM Consortium welcomes 3 DOE national labs to accelerate drug discovery

March 29, 2021- 
The Accelerating Therapeutics for Opportunities in Medicine (ATOM) consortium, of which LLNL is part, announced the U.S. Department of Energy’s Argonne, Brookhaven and Oak Ridge national laboratories are joining the consortium to further develop ATOM’s AI-driven drug discovery platform. The public-private ATOM consortium aims to transform drug discovery from a slow, sequential and high-risk...

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...

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...