Topic: Data Science

Livermore’s machine learning experts aim to provide assurances on performance and enable trust in machine-learning technology through innovative validation and verification techniques.

For the first time in the DSC series since the COVID-19 pandemic began in 2020, Lab mentors visited the college campus to provide in-person guidance for five teams of UC Merced students.

The Accelerating Therapeutic Opportunities in Medicine (ATOM) consortium is showing “significant” progress in demonstrating that HPC and machine learning tools can speed up the drug discovery process, ATOM co-lead Jim Brase said at a recent webinar.

Winning the best paper award at PacificVis 2022, a research team has developed a resolution-precision-adaptive representation technique that reduces mesh sizes, thereby reducing the memory and storage footprints of large scientific datasets.

LLNL participates in the International Parallel and Distributed Processing Symposium (IPDPS) on May 30 through June 3.

LLNL and the United Kingdom’s Hartree Centre are launching a new webinar series intended to spur collaboration with industry through discussions on computational science, HPC, and data science.

Kevin McLoughlin has always been fascinated by the intersection of computing and biology. His LLNL career encompasses award-winning microbial detection technology, a COVID-19 antiviral drug design pipeline, and work with the ATOM consortium.

Technologies developed through the Next-Generation High Performance Computing Network project are expected to support mission-critical applications for HPC, AI and ML, and high performance data analytics.

The Exascale Computing Project (ECP) 2022 Community Birds-of-a-Feather Days will take place May 10–12 via Zoom. The event provides an opportunity for the HPC community to engage with ECP teams to discuss our latest development efforts.

LLNL celebrated the 2022 Global Women in Data Science conference on March 7 with its 5th annual regional event, featuring workshops, mentoring sessions and a discussion with LLNL Director Kim Budil.

Sponsored by the DSI, LLNL’s winter hackathon took place on February 16–17. 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.

Registration is open until February 27 for LLNL's fifth annual WiDS event in conjunction with the worldwide Women in Data Science conference.

The Department of Energy's Office of Science interviewed LLNL computer scientist Peter Lindstrom about his work since receiving the 2011 Early Career Award.

LivIT tackles challenges of workforce safety, telecommuting, cyber security protocols, National Ignition Facility software updates, and more.

From molecular screening, a software platform, and an online data to the computing systems that power these projects.

LLNL’s cyber programs work across a broad sponsor space to develop technologies addressing sophisticated cyber threats directed at national security and civilian critical infrastructure.

LC sited two different AI accelerators in 2020: the Cerebras wafer-scale AI engine attached to Lassen; and an AI accelerator from SambaNova Systems into the Corona cluster.

This project advances research in physics-informed ML, invests in validated and explainable ML, creates an advanced data environment, builds ML expertise across the complex, and more.

LLNL researchers and collaborators have developed a highly detailed, ML–backed multiscale model revealing the importance of lipids to RAS, a family of proteins whose mutations are linked to many cancers.

Highlights include power grid challenges, performance analysis, complex boundary conditions, and a novel multiscale modeling approach.

LLNL has established the AI Innovation Incubator (AI3), a collaborative hub aimed at uniting experts from LLNL, industry, and academia to advance AI for scientific and commercial applications.

For the first time ever, SC21 went hybrid, with dozens of both in-person and virtual workshops, technical paper presentations, panels, tutorials and “birds of a feather” sessions.

The Data Science Institute hosted a career panel featuring members of some of LLNL's Employee Resource Groups: Asian Pacific American Council, Amigos Unidos Hispanics in Partnership, Women’s Association, and Abilities Champions.

LLNL is participating in the 33rd annual Supercomputing Conference (SC21), which will be held both virtually and in St. Louis on November 14–19, 2021.

An LLNL mathematician and collaborators have developed a machine learning–based technique capable of deriving a mathematical model for the motion of binary black holes from gravitational wave data.