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2026 Alvarez Fellow Samson Wang Bridges Quantum Theory and Practice

Samson Wang smiling warmly at the camera while standing outdoors in front of a backdrop of dense green leaves. They have short dark hair with bangs and are wearing round wire-rimmed glasses and an olive green button-down shirt.

Samuel Williams Honored with E.O. Lawrence Award

Headshot of Berkeley Lab senior scientist Samuel Williams.

Marcus Noack Receives 2026 DOE Early Career Award

A headshot of Marcus Noack smiling, wearing a dark green knit sweater with wooden toggle buttons, standing against a blurred architectural background.

Paul Hargrove Reflects on 27 Years at Berkeley Lab

A professional headshot of Paul Hargrove with long brown hair pulled back into a ponytail. He is wearing wire-rimmed glasses and a dark polo shirt against a mottled gray background.

Expert Insight: Keith Beattie and the Rise of the RSE

Excited-States Framework Could Illuminate New Optical Materials

NERSC Director Sudip Dosanjh to Retire

A Berkeley Lab Mentorship Comes Full Circle

Three people stand smiling for a photo outside the entrance of a modern, grey-paneled building labeled "Shyh Wang Hall". From left to right: a man wearing sunglasses and a pink polo shirt, a woman wearing sunglasses and a bright yellow patterned top, and a young man wearing a black denim jacket over a black shirt with blue jeans. They are standing on a wide concrete walkway on a bright, sunny day.

DL4SCI Brings Researchers Into the Data Lifecycle

Two pairs of researchers discuss their work at a poster session

Novel Family of Conditional Generative Models Uses AI-Generated Earthquake Simulations to Improve Disaster Preparedness

A three-part diagram illustrating the workflow of the Conditional Generative Modeling for Ground Motion (CGM-GM) AI model. The left section shows a map of the San Francisco Bay Area with a red star marking an earthquake source and blue triangles representing seismic stations. The middle section features a three-dimensional, hourglass-shaped wireframe representing the CGM-GM model, compressing blue input data on the left into a narrow bottleneck and expanding it into red output data on the right. Below the model, three text boxes with icons indicate the system is trained on regional data, captures wave propagation, and accounts for subsurface heterogeneity. The right section displays the model's outputs: a heat map showing generated shaking intensity radiating from the earthquake source, with a color scale ranging from blue for low intensity to red for high intensity, and a line graph below it showing the detailed waveform of the generated ground motion.

Pele Combustion Simulation Suite Named R&D 100 Award Winner

A high-resolution 3D computer simulation of a turbulent flame expanding from left to right against a light grey background. The simulation shows a textured, silver-grey plume of fuel igniting into a bright core of blue, red, orange, and yellow colors representing intense heat and complex chemical reactions. In the top left corner is a black and gold badge that reads R&D 100 WINNER.

Software Highlight: AstraAI Masters the Complex Rules of Scientific HPC Software

A flowchart outlining the system architecture for AstraAI. The process begins on the left with a natural language user prompt, which is passed to an LLM for user intent extraction utilizing run-time tools like Hugging Face, Llama.cpp, or Ollama. The workflow then splits into two parallel processes: Retrieval Augmented Generation to extract relevant code chunks, and Abstract Syntax Tree code structure extraction utilizing Clang tools like intercept_build and clang-query. The outputs from these two processes are merged into a final prompt that includes the original user prompt, the RAG chunks, and the structure information. This final prompt is sent to an LLM for code generation, which ultimately leads to AST-safe code editing featuring GitHub conflict-style markers.
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