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“Debfest,” Celebrating Deb Agarwal’s Contributions to Science and Berkeley Lab Culture

July 17, 2023

On Friday, July 7, former Scientific Data Division Director Deb Agarwal’s family, friends, and colleagues gathered at UC Berkeley’s Faculty Club to celebrate her 29-year career and contributions to Berkeley Lab Computing Sciences area—an event jokingly dubbed “Debfest.” Read More »

Using Deep Learning to Better Assess Lithium Metal Battery Performance

July 14, 2023

A team of researchers from CAMERA, Berkeley Lab, UC Irvine, and Argonne have developed batteryNET, a deep learning algorithm that enhances the assessment of lithium agglomeration in solid-state lithium metal batteries. Read More »

Craig Leres to Retire after 40+ Years with Berkeley Lab

July 11, 2023

Craig Leres, a hardware, operating systems, and networking engineer in the Berkeley Lab Computing Sciences Area’s Scientific Data Division and the Lab’s Cyber Security Group, is retiring this July after 40-plus years at the Lab. Read More »

Peter Schwartz Retires from Berkeley Lab after 22 Years in Computing Sciences

July 11, 2023

For Peter Schwartz, a research scientist who joined the Computing Sciences Area’s Applied Numerical Algorithms Group in 2001, math has long been a pathway. Now, after 20+ years at Berkeley Lab, Schwartz is moving on to his next adventure. Read More »

A Data Science Pioneer, Deb Agarwal Retires From Berkeley Lab

July 6, 2023

After a distinguished Berkeley Lab career spanning nearly three decades, Scientific Data Division (SciData) Director Deborah Agarwal retired on July 1. Deb has played a pivotal role in using computer and data science to address the needs of diverse scientific communities and laid a strong foundation for Berkeley Lab to lead in the field of data science. Read More »

Berkeley Lab Celebrates 20 Years of the Alvarez Fellowship

June 6, 2023

This year, Lawrence Berkeley National Laboratory (Berkeley Lab) is celebrating yet another milestone: the 20th anniversary of the Luis W. Alvarez Fellowship in Computing Sciences. Read More »

Berkeley Lab Computing Sciences Takes Novel Approach to Science Workforce Development and Diversity

May 31, 2023

The Sustainable Research Pathways (SRP) program has been connecting students from underrepresented communities and institutions to scientists and staff at Berkeley Lab for nearly a decade to facilitate research collaborations and bolster workforce development and diversity, equity, and inclusion. Read More »

Berkeley Lab’s Novel Method for Modeling Fluids at the Mesoscale

May 22, 2023

Recently, Berkeley Lab researchers developed a continuum FHD model that efficiently harnesses the power of cutting-edge exascale supercomputers to simulate the transport phenomenai n fluid mixtures. Read More »

Quantum-Inspired Artwork Unveiled

April 18, 2023

For World Quantum Day on April 14, Berkeley Lab’s Computing Sciences Area celebrated the interdisciplinary collaboration between the Advanced Quantum Testbed (AQT) at Berkeley Lab and the California-based contemporary visual artist Benjamin Arizmendi. Read More »

Quantum Evolution

April 13, 2023

A leading expert in quantum computing, Bert de Jong discusses why quantum computing matters, where it is today, and the potential of this emerging technology to change science. Read More »

Berkeley Lab Researchers Awarded ISQED’23 Best Paper

April 4, 2023

The International Symposium on Quality Electronic Design (ISQED’23) recognized researchers in Lawrence Berkeley National Laboratory’s (Berkeley Lab’s) Computer Architecture Group with a Best Paper Award for “An Area Efficient Superconducting Unary CNN Accelerator.” Read More »

New Math Methods and Perlmutter HPC Combine to Deliver Record-Breaking ML Algorithm

March 13, 2023

Using the Perlmutter supercomputer at the National Energy Research Scientific Computing Center (NERSC), researchers at Lawrence Berkeley National Laboratory (Berkeley Lab) have devised a new mathematical method for analyzing extremely large datasets – and, in the process, demonstrated proof of principle on a record-breaking dataset of more than five million points. Read More »

Improving Training for Scientific Machine Learning

March 3, 2023

In the world of scientific machine learning (SciML), scientists are beginning to embrace the use of neural networks as a way to accelerate simulations. At the heart of deep learning algorithms, neural networks provide a mechanism to encode complex dependency structures, using many connected node layers to transform data into learned features to be used for a wide range of scientific tasks. Read More »

The Most Advanced Bay Area Earthquake Simulations Will be Publicly Available

February 10, 2023

A collaboration involving scientists and computing resources from Berkeley Lab and the simulation software EQSIM is releasing the most accurate and detailed earthquake simulations to date, which will initially capture earthquake motions across the San Francisco Bay Area and later expand to other regions. Read More »

WarpX Code Shines at the Exascale Level

February 2, 2023

The WarpX project has spent the last six years creating a novel, highly parallel, and highly optimized single-source simulation code for modeling plasma-based particle colliders on cutting-edge exascale supercomputers, with broad importance for other accelerators and related problems. Read More »

Berkeley Lab Scientists Create Machine Learning Pipeline for Interpreting Large Tomography Datasets

January 25, 2023

A group of Berkeley Lab scientists has developed and tested several machine learning techniques organized in a learning pipeline to improve the interpretation of increasingly large cryo-ET datasets. Read More »

Berkeley Lab’s Ushizima Honored with PMWC Pioneer Award

January 25, 2023

Berkeley Lab’s Daniela Ushizima was recognized with PMWC Pioneer Award for constructing “a new and reliable technique for diagnosing Alzheimer’s disease and measuring the efficacy of experimental treatments.” Read More »

The SciData Division’s Jean Luca Bez Receives BSSw Honorable Mention

January 9, 2023

Jean Luca Bez, a postdoctoral scholar in the Scientific Data Management Research (SDMR) group was recognized with an Honorable Mention by the Better Scientific Software (BSSw) Fellowship Program. Read More »

Bert de Jong Named 2023 Oppenheimer Fellow

December 13, 2022

Bert de Jong has been selected as a 2023 fellow of the Oppenheimer Science and Energy Leadership Program (OSELP). Read More »

Berkeley Lab’s Networking Middleware GASNet Turns 20

December 5, 2022

For 20 years, Berkeley Lab’s GASNet has been fueling developers’ ability to tap the power of massively parallel supercomputers more effectively. The middleware was recently upgraded to support exascale scientific applications. Read More »

HUNTRESS: A Step Forward for Computational Oncology Data Analysis

November 30, 2022

The latest developments in computational oncology are giving medical researchers a glimpse into a future where they’ll be able to understand tumor progression via supercomputers and advanced mathematical algorithms. Read More »

SCGSR Fellow Brings Astrophysics Data Skills to Berkeley Lab and Black Holes

November 28, 2022

Graduate student Peter Craig spent much of 2022 working with researchers in the Berkeley Lab Applied Mathematics and Computational Research division scouring through a new, massive astrophysics dataset looking for previously unidentified binary black holes. Read More »

Berkeley Lab-Led WarpX Project Key to 2022 Gordon Bell Prize

November 18, 2022

A Berkeley Lab research team and international collaborators were awarded the prestigious ACM Gordon Bell Prize on November 17 during SC22. Read More »

Stefan Wild to Lead Berkeley Lab’s Applied Mathematics and Computational Research Division

November 2, 2022

Stefan Wild has been selected to serve as the next director for Berkeley Lab's Applied Mathematics and Computational Research (AMCR) Division in the Computing Sciences Area (CSA). Read More »

Berkeley Lab Scientists Win IEEE LDAV Best Paper Award

November 1, 2022

Berkeley Lab scientists were honored with a Best Paper Award by the IEEE Large Scale Data Analysis and Visualization (LDAV) symposium. Their paper, Distributed Hierarchical Contour Trees, discusses their development of a powerful tool for data analysis. Read More »