
Filter News
News Type
News Topics
- (-) National Security (2)
- (-) Physics (1)
- 3-D Printing/Advanced Manufacturing (3)
- Advanced Reactors (2)
- Artificial Intelligence (5)
- Big Data (4)
- Biology (1)
- Biomedical (1)
- Buildings (2)
- Computer Science (11)
- Cybersecurity (1)
- Energy Storage (1)
- Exascale Computing (3)
- Frontier (1)
- Grid (2)
- High-Performance Computing (7)
- Machine Learning (3)
- Materials Science (1)
- Mathematics (1)
- Microscopy (1)
- Neutron Science (1)
- Nuclear Energy (4)
- Partnerships (1)
- Quantum Computing (3)
- Quantum Science (3)
- Security (1)
- Simulation (1)
- Software (1)
- Space Exploration (1)
- Summit (4)
- Transportation (2)
Media Contacts

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.
Joe Tuccillo, a human geography research scientist, leads the UrbanPop project that uses census data to create synthetic populations. Using a Python software suite called Likeness on ORNL’s high-performance computers, Tuccillo’s team generates a population with individual ‘agents’ designed to represent people that interact with other agents, facilities and services in a simulated neighborhood.

Walters is working with a team of geographers, linguists, economists, data scientists and software engineers to apply cultural knowledge and patterns to open-source data in an effort to document and report patterns of human movement through previously unstudied spaces.