Filter News
Area of Research
News Topics
- (-) 3-D Printing/Advanced Manufacturing (1)
- (-) Artificial Intelligence (4)
- (-) Grid (2)
- (-) Security (2)
- Big Data (2)
- Bioenergy (3)
- Biology (4)
- Biomedical (2)
- Biotechnology (1)
- Buildings (1)
- Climate Change (6)
- Computer Science (7)
- Coronavirus (3)
- Cybersecurity (2)
- Decarbonization (1)
- Environment (3)
- Exascale Computing (1)
- Frontier (3)
- High-Performance Computing (5)
- Machine Learning (4)
- Materials (4)
- Materials Science (3)
- Microscopy (1)
- Nanotechnology (2)
- National Security (7)
- Neutron Science (2)
- Quantum Computing (5)
- Quantum Science (3)
- Simulation (3)
- Summit (4)
- Sustainable Energy (1)
Media Contacts
In human security research, Thomaz Carvalhaes says, there are typically two perspectives: technocentric and human centric. Rather than pick just one for his work, Carvalhaes uses data from both perspectives to understand how technology impacts the lives of people.
When the COVID-19 pandemic stunned the world in 2020, researchers at ORNL wondered how they could extend their support and help
How an Alvin M. Weinberg Fellow is increasing security for critical infrastructure components
It’s a simple premise: To truly improve the health, safety, and security of human beings, you must first understand where those individuals are.
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.
A study led by researchers at ORNL could help make materials design as customizable as point-and-click.
Unequal access to modern infrastructure is a feature of growing cities, according to a study published this week in the Proceedings of the National Academy of Sciences
A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.