Jonathan Carter, a light haired person wearing a blue collared shirt, poses for a headshot outdoors.

Advanced computing technologies

Beyond Moore’s Law / frontiers of computing

Superfacility / self-driving labs

Data science

Software enabling science

Quantum computing

Modeling and simulation

Decorative panels on the exterior of the computer cabinets for the Perlmutter NERSC-9. World map with interconnecting lines. CAMERA scientific figure. Close-up view of a microchip. Lavanya Ramakrishnan, a person with medium-length black hair wearing a pale pink collared shirt, photographed indoors against a gray backdrop.

Lavanya Ramakrishnan is a senior scientist and division deputy in the Scientific Data Division within the Computing Sciences Area. Her research interests are in building software tools for computational and data-intensive science with a focus on workflow, resource, and data management.

Marcus Noack, a person with short brown hair wearing a purple shirt against a white, digital background with mathematical formulas and symbols floating around.

Marcus Noack is a research scientist in the Applied Mathematics and Computational Research Division focusing on mathematical theory and algorithms for uncertainty quantification and autonomous experimentation. He developed gpCAM, a software widely used in applications across many experimental facilities around the globe.

Katie Klymko, a person with long brown hair pulled back into a braided ponytail, wearing a gray shirt. Katie is photographed indoors against a gray backdrop.

Katie Klymko is a staff member in NERSC's Advanced Technologies Group working to integrate HPC and quantum computing. Her previous work focused on the development of efficient methods for eigenvalue calculations in molecular systems as well as quantum computing algorithms to explore thermodynamic properties.

Group of three people excavating for an ESNet upgrade. Person with dark hair and a pink turban stands in front of a blue building.

The Energy Sciences Network (ESnet) announced that it has supercharged the current and future bandwidth for four of the Department of Energy’s (DOE’s) national laboratories and user facilities, unleashing 400 Gigabit per second (400G) capability for Argonne National Laboratory, National Energy Research Scientific Computing Center, Oak Ridge National Laboratory, and Pacific Northwest National Laboratory.

Berkeley Lab Research Scientist Mariam Kiran uses deep reinforcement learning and innovative multi-objective optimization techniques to train network controllers to predict network traffic and improve traffic engineering.

In our very first episode, we discuss machine learning (ML). First developed about 80 years ago, ML is a type of artificial intelligence centered on programs — called algorithms — that can teach themselves different ways of processing data after they are trained on sample data sets.


A small brown wooden model of a house sits on cracked concrete A human-perspective of a large warehouse holding a soil box seismic activity system. Rainfall at a beach. Colorful, abstract nebulous image. Charlie Koven conducting fieldwork outdoors. Photo of gloved handed adjusting a quantum fridge with gloved hands and instruments.