Data Science in the News

LLNL’s Brase discusses advances by ATOM in accelerating drug discovery pipeline

June 7, 2022- 
The private-public Accelerating Therapeutic Opportunities in Medicine (ATOM) consortium is showing “significant” progress in demonstrating that HPC and M) tools can speed up the drug discovery process, said Jim Brase, ATOM co-lead and LLNL’s deputy associate director for data science. The consortium currently boasts more than a dozen member organizations, including national laboratories...

CASC team wins best paper at visualization symposium

May 25, 2022- 
A research team from LLNL’s Center for Applied Scientific Computing won Best Paper at the 15th IEEE Pacific Visualization Symposium (PacificVis), which was held virtually on April 11–14. Computer scientists Harsh Bhatia, Peer-Timo Bremer, and Peter Lindstrom collaborated with University of Utah colleagues Duong Hoang, Nate Morrical, and Valerio Pascucci on “AMM: Adaptive Multilinear Meshes.”...

Kevin McLoughlin applies computational biology to complex problems

May 17, 2022- 
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. The appeal for him in these projects lies at the intersection of computing and biology. “I love finding ways to visualize data that reveal relationships...

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...

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...

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.

Visualization software stands the test of time

Sept. 13, 2021- 
In the decades since LLNL’s founding, the technology used in pursuit of the Laboratory’s national security mission has changed over time. For example, studying scientific phenomena and predicting their behaviors require increasingly robust, high-resolution simulations. These crucial tasks compound the demands on high-performance computing hardware and software, which must continually be...

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...

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...

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...

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...

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...

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...

Looking ahead to SC20

Oct. 27, 2020- 
Lawrence Livermore heads to the 32nd annual Supercomputing Conference (SC20) held virtually throughout November 9–19. Be sure to follow LLNL Computing (@Livermore_Comp) on Twitter with these hashtags: #LLNLatSC, #SC20, #MoreThanHPC. The Department of Energy (@NatLabsHPC) will also tweet during the event. Much of the content is pre-recorded and will remain available online for six months...

Harsh Bhatia uses scientific visualization to see the unseen

Oct. 6, 2020- 
Harsh Bhatia is a computer scientist at the Center for Applied Scientific Computing (CASC) where he has made a name for himself in data analysis, scientific visualization, and machine learning. His wide range of projects include applying topological techniques to understand the behavior of lithium ions, generating topological representations of aerodynamics data, and analyzing and visualizing...

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...

UC Merced students receive NSF research fellowships

June 3, 2020- 
Maia Powell, a PhD student in Applied Mathematics at UC Merced, has been awarded a National Science Foundation Graduate Research Fellowship. Powell participated in the DSI's Data Science Challenge this summer, serving as a team lead for other students. Read more at UC Merced.

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...