John Wu, a dark-haired person wearing a gray suit, poses for a headshot against a gray background.

Applied math

Developing novel mathematical methods and efficient computing algorithms to solve critical problems in science and engineering.

Modeling and simulation

Delivering innovative, effective multiscale modeling and simulation solutions in a variety of scientific areas.

Machine learning / AI

Developing novel, robust, and interpretable AI and learning methods; applying and adapting advances in AI to the complexity of science; enabling the deployment of AI applications at large computing scales.

Software enabling science

Developing sustainable software packages for modeling and simulation, computer science, and data science to enable scientific discovery.

Data science

Transforming data-driven discovery and understanding by developing and applying novel data science methods, technologies, and infrastructures with scientific partners.

 Decorative panels on the exterior of the computer cabinets for the Perlmutter NERSC-9.

NERSC provides computational and data resources and expertise to scientists performing open-science research.

 World map with interconnecting lines.

ESnet performs research and provides high-bandwidth network connections to meet the exceptional data demands of DOE science.

 CAMERA scientific figure.

CAMERA is an integrated, cross-disciplinary center that aims to invent, develop, and deliver the fundamental new mathematics required to capitalize on experimental investigations at scientific facilities.

 Michael Mahoney, a light-haired person wearing a brown suit, speaks into a microphone onstage.

“Berkeley Lab is unique because its machine learning expertise is reasonably well established, and its tradition of team science means that we can work with researchers to apply these methods to scientific problems.”

Sherry Li, a dark haired person wearing a black sweater, poses for a headshot in front of a whiteboard.

“Although much of the time and effort spent in the software maintenance is not reflected in our research publication list, it is more than rewarding to see the wide use of this software in both the high-end scientific world and the commercial world.”

 Ann Almgren, a brown-haired person wearing a dark shirt, smiles for a headshot outdoors.

“I think one of the things Berkeley Lab does well is allow people to make collaborations that advance science much more efficiently.”

Graphical illustration of network connections. Gerbrand Ceder, a dark-haired person wearing a black turtleneck, poses for a headshot.

Berkeley Lab’s research into machine learning builds on its foundational work in mathematics to develop methods that are consistent with physical laws, robust in the presence of noisy or biased data, and capable of being interpreted and explained in scientifically meaningful ways.

First developed about 80 years ago, machine learning is a type of AI centered on programs — called algorithms — that can teach themselves different ways of processing data after they are trained on sample datasets.

 Aerial view of atmospheric rivers developing over the Pacific. Illustration of a robot arm, vials, a laptop, and a beaker on a desk facing the window. 3d rendered image of a brain on a dark background. Glowing abstract digital neuron connections and plexus lines scatter around the brain and dissipate to the edges. CPU desktop with the contacts facing up lying on the motherboard of the PC. the chip is highlighted with blue light. Technology background Aerial views of Berkeley Lab made using an aerial photography drone. Kristin Persson, a brown-haired person wearing a black dress, points at her electrolyte genome 3D visualizations.