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Improving Training for Scientific Machine Learning

CS Area Research Shines at 2023 Postdoc Symposium

Hengrui Luo was one of 18 who presented their research during the 2023 CS Area Postdoc Symposium. (Credit: Margie Wylie, Berkeley Lab)

The Most Advanced Bay Area Earthquake Simulations Will be Publicly Available

Modeling the effects of earthquakes on homes, businesses, and infrastructure is about to get a lot easier, thanks to advanced simulations performed on the world's fastest supercomputers. (Credit: SUNGYOON/Adobe Stock)

Berkeley Lab Researchers Share Expertise at SIAM’s CSE23

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

3D rendering of six regions obtained via the machine learning pipeline developed by Berkeley Lab scientists to improve cryo-ET image data analysis. Each region is labeled by a unique color.

EQSIM Shakes Up Earthquake Research at the Exascale Level

Figure 1. The multiscale computational challenge of fault-to-structure simulations starting from the earthquake source, continuing through regional-scale wave propagation in a heterogeneous earth at a scale of hundreds of kilometers (“Regional geophysics domain”) and ending at local interaction between complex incident seismic waves with a soil-structure system at a scale of 30–50 m (“Local engineering system domain”). (Credit: David McCallen)

CS Staff to Present at 2022 American Geophysical Union Meeting

SC22 Recap: For Berkeley Lab, a Gordon Bell Prize Win and More

Berkeley Lab Scientists Win IEEE LDAV Best Paper Award

Sharing a Common Data Format for Neurophysiology

(Credit: Allen Institute for Brain Science)

Future-Oriented Report Contributes a Next Step in the Application of Computing to Scientific Discovery

Summer Research Program Wraps with Poster Sessions

Muna Tageldin, a Ph.D. student from Marquette University, presents her research at the culminating poster session for the 2022 CSA Summer Program.
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