Building on Berkeley Lab’s rich tradition of team science, we combine deep expertise in mathematics, statistics, computing, and data sciences with a wide range of scientific disciplines to drive AI innovation. We collaborate with researchers across domains to generate, process, and curate vast datasets, which serve as critical resources for scientific discovery.
In parallel, we develop and deploy cutting-edge AI models and tools. By adapting existing machine learning methods and creating new ones, we address the diverse, evolving needs of scientific research, answering fundamental questions and enabling breakthroughs across various fields. These AI models are applied to solve complex scientific problems and accelerate discovery in key research areas.
Our efforts are supported by robust high-performance computing and networking infrastructure. We operate the Department of Energy’s National Energy Research Scientific Computing Center (NERSC) and the Energy Sciences Network (ESnet), which provide the computational power, data storage, and remote access necessary for AI training, large-scale simulations, and collaborative research at distant experimental facilities.
Our Research Pillars:
- New Models and Methods
- Learning for Scientific Discovery
- Supercomputing-Scale AI
- Secure Machine Learning & ML for Security
- Statistics and Applied Mathematics
- Data and Science Informed Learning
