In response to a Department of Energy grid optimization challenge, the LLNL-led gollnlp team is developing the mathematical, computational, and software components needed to solve problems of the real-world power grid.
Data Analytics and Management
Data Analytics and Management is the branch of computer science that is concerned with extracting usable information from data. At LLNL, we’re working with data in many forms: text, images, videos, semantic graphs, and more. This data may be “at rest” in files or databases, or “in motion” as it streams in from sensors or other live sources. Our informatics research aims to gain insight from data that is very large, geographically distributed, complex, fast moving, or some combination of these characteristics. Applications for this work span a wide range of LLNL missions, including energy security and efficiency, biosecurity, computer security, and climate change. View content related to Data Analytics and Management.
New year, new hackathon! The January 30–31 event was Computing’s 23rd hackathon and the 1st scheduled in the winter season.
A multi-institutional consortium aims to speed up the drug discovery pipeline by building predictive, data-driven pharmaceutical models.
Rafael Rivera-Soto is passionate about artificial intelligence, deep learning, and machine learning technologies. He works in LLNL’s Global Security Computing Applications Division, also known as GSCAD.