Shreyas Cholia has been invited by the National Academies of Sciences, Engineering, and Medicine to serve as a member for the Realizing Opportunities for Advanced and Automated Workflows in Scientific Research committee.
The Future of Machine Learning, Data Analytics
Modeling the Melting Antarctic Ice Sheet
UniviStor: Next-generation Data Storage for HPC
IDAES Software Goes Open Source
New Group Taps Lab's Biology and Computing Strengths
On May 1, a group of students from UC Merced, all participants in the National Science Foundation’s Interdisciplinary Computational Graduate Education program, visited Berkeley Lab to learn about the many ways computing can be applied to research problems.
Early to mid-career national lab mathematicians met at Berkeley Lab to discuss challenges in machine learning and data analytics and to seed new collaborations.
Researchers in Berkeley Lab's Computational Research Division are applying deep learning methods and data analytics to electronic health record data to help the Veterans Administration address a host of medical and psychological challenges affecting many of the nation’s 700,000 military veterans.
The Proactive Data Containers project team at Berkeley Lab is developing object-oriented I/O services designed to simplify data movement, data management, and data reading services on next-generation HPC architectures.
IDAES has released the first open-source version of its next-generation computational framework and model library, created to optimize the design of process systems engineering solutions used to model advanced energy systems.