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Michelle Kidder received the lab’s Director’s Award for Outstanding Individual Accomplishment in Science and Technology for her decades-long work mentoring students, teachers and early-career staff. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Laboratory Director Thomas Zacharia presented five Director’s Awards during Saturday night's annual Awards Night event hosted by UT-Battelle, which manages ORNL for the Department of Energy.

ORNL scientists created a geodemographic cluster for the Atlanta metro area that identifies risk factors related to climate impacts. Credit: ORNL/U.S. Dept. of Energy

A new capability to identify urban neighborhoods, down to the block and building level, that are most vulnerable to climate change could help ensure that mitigation and resilience programs reach the people who need them the most.

LandScan Global depicts population distribution estimates across the planet. The darker orange and red colors above indicate higher population density. Credit: ORNL, U.S. Dept. of Energy

It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.

ORNL, VA and Harvard researchers developed a sparse matrix full of anonymized information on what is thought to be the largest cohort of healthcare data used for this type of research in the U.S. The matrix can be probed with different methods, such as KESER, to gain new insights into human health. Credit: Nathan Armistead/ORNL, U.S. Dept. of Energy

A team of researchers has developed a novel, machine learning–based  technique to explore and identify relationships among medical concepts using electronic health record data across multiple healthcare providers.

Dongarra in 2019 with Oak Ridge National Laboratory's Summit supercomputer

A force within the supercomputing community, Jack Dongarra developed software packages that became standard in the industry, allowing high-performance computers to become increasingly more powerful in recent decades.

Project bridges compute staff, resources at ORNL and VA health data to speed suicide risk screening for US veterans. Image Credit: Carlos Jones, ORNL

In collaboration with the Department of Veterans Affairs, a team at Oak Ridge National Laboratory has expanded a VA-developed predictive computing model to identify veterans at risk of suicide and sped it up to run 300 times faster, a gain that could profoundly affect the VA’s ability to reach susceptible veterans quickly. 

Heat impact map

A detailed study by Oak Ridge National Laboratory estimated how much more—or less—energy United States residents might consume by 2050 relative to predicted shifts in seasonal weather patterns 

Computing—Building a brain

Researchers at Oak Ridge National Laboratory are taking inspiration from neural networks to create computers that mimic the human brain—a quickly growing field known as neuromorphic computing.

Computing—Routing out the bugs

A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool

As part of a preliminary study, ORNL scientists used critical location data collected from Twitter to map the location of certain power outages across the United States.

Gleaning valuable data from social platforms such as Twitter—particularly to map out critical location information during emergencies— has become more effective and efficient thanks to Oak Ridge National Laboratory.