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ORNL researcher Priya Ranjan standing outside in front of brick pillars

From decoding plant genomes to modeling microbial behavior, computational biologist Priya Ranjan builds computational tools that turn extensive biological datasets into real-world insights. These tools transform the way scientists ask and answer complex biological questions that advance biotechnology breakthroughs and support cultivation of better crops for energy and food security. 

Illustration of the GRETA detector, a spherical array of metal cylinders. The detector is divided into two halves to show the inside of the machine. Both halves are attached to metal harnesses, displayed against a black and green cyber-themed background.

Analyzing massive datasets from nuclear physics experiments can take hours or days to process, but researchers are working to radically reduce that time to mere seconds using special software being developed at the Department of Energy’s Lawrence Berkeley and Oak Ridge national laboratories.  

Wall of black computer chords with blue wiring

Researchers from ORNL have developed a new application to increase efficiency in memory systems for high performance computing. Rather than allow data to bog down traditional memory systems in supercomputers and impact performance, the team from ORNL, along with researchers from the University of Tennessee, Knoxville, created a framework to manage data more efficiently with memory systems that employ more complex structures. 

ORNL R&D data scientist Max Pasini is posing for a portrait with a blue background, black button up long sleeve shirt

Massimiliano (Max) Lupo Pasini, an R&D data scientist from ORNL, was awarded the National Energy Research Scientific Computing Center’s High Performance Computing Achievement Award for High Impact Scientific Achievement for his work in “Groundbreaking contributions to scientific machine learning, particularly through the development of HydraGNN.”

Image is blue and green with the background being a building on the left, merging into the photo on the right which are pictures of doppler radar graphics

Researchers at the Department of Energy’s Oak Ridge National Laboratory are using non-weather data from the nationwide weather radar network to understand how to track non-meteorological events moving through the air for better emergency response. 

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As hurricanes barrel toward the coastlines and wildfires rage in arid regions of the United States, scientists at the Department of Energy’s Oak Ridge National Laboratory are providing critical geospatial data to support first responders as they work to save lives and property.

Jay Jay Billings and Alex McCaskey observe visualizations of ICE simulation data on ORNL’s Exploratory Visualization Environment for Research in Science and Technology facility. Credit: Jason Richards/ORNL
Since designing and launching a specialized workflow management system in 2010, a research team from the U.S. Department of Energy’s Oak Ridge National Laboratory has continuously updated the technology to help computational scientists develop software, visualize data and solve ...
Singanallur “Venkat” Venkatakrishnan is a Wigner Fellow in the Imaging, Signals, and Machine Learning Group at ORNL.
Singanallur “Venkat” Venkatakrishnan is helping scientists get a better view of objects under study by some of Oak Ridge National Laboratory’s most powerful instruments by creating algorithms that turn data into 3D renderings with fewer images. The result is a better understanding o...
The ORNL-developed site assessment tool, dubbed SMH Explorer, provides a platform to develop small modular hydropower technologies by identifying common physical and environmental characteristics in stream segments across the nation. Credit: Oak Ridge Nat

Oak Ridge National Laboratory has created new tools to better understand the nation’s waterways and identify potential sites to generate hydropower—a domestic renewable energy resource. The tools allow users such as scientists, resource agencies and industry to access information ab...