Filter News
Area of Research
News Type
News Topics
- (-) Mathematics (4)
- 3-D Printing/Advanced Manufacturing (30)
- Advanced Reactors (6)
- Artificial Intelligence (48)
- Big Data (18)
- Bioenergy (32)
- Biology (40)
- Biomedical (12)
- Biotechnology (11)
- Buildings (27)
- Chemical Sciences (36)
- Clean Water (8)
- Climate Change (50)
- Composites (10)
- Computer Science (40)
- Coronavirus (4)
- Critical Materials (9)
- Cybersecurity (9)
- Decarbonization (49)
- Education (4)
- Emergency (2)
- Energy Storage (29)
- Environment (61)
- Exascale Computing (20)
- Fossil Energy (4)
- Frontier (25)
- Fusion (13)
- Grid (22)
- High-Performance Computing (46)
- Hydropower (3)
- Irradiation (2)
- Isotopes (21)
- ITER (1)
- Machine Learning (23)
- Materials (72)
- Materials Science (28)
- Mercury (2)
- Microelectronics (2)
- Microscopy (9)
- Molten Salt (1)
- Nanotechnology (9)
- National Security (34)
- Net Zero (10)
- Neutron Science (41)
- Nuclear Energy (28)
- Partnerships (34)
- Physics (16)
- Polymers (9)
- Quantum Computing (20)
- Quantum Science (19)
- Renewable Energy (2)
- Security (5)
- Simulation (40)
- Software (1)
- Space Exploration (7)
- Statistics (2)
- Summit (13)
- Sustainable Energy (33)
- Transportation (28)
Media Contacts
![Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.](/sites/default/files/styles/list_page_thumbnail/public/2024-06/2024-P09065.jpg?h=036a71b7&itok=szEF_SdO)
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
![ORNL’s Suhas Sreehari explains the algebraic and topological foundations of representation systems, used in generative AI technology such as large language models. Credit: Lena Shoemaker/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/powered%20by%20match.jpg?h=384e2afb&itok=wJegcDZm)
In the age of easy access to generative AI software, user can take steps to stay safe. Suhas Sreehari, an applied mathematician, identifies misconceptions of generative AI that could lead to unintentionally bad outcomes for a user.
![Saubhagya Rathore uses his modeling, hydrology and engineering expertise to improve understanding of the nation’s watersheds to better predict the future climate and to guide resilience strategies. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-07/2023-P08731.jpg?h=c6980913&itok=H4Aq_dfv)
Growing up exploring the parklands of India where Rudyard Kipling drew inspiration for The Jungle Book left Saubhagya Rathore with a deep respect and curiosity about the natural world. He later turned that interest into a career in environmental science and engineering, and today he is working at ORNL to improve our understanding of watersheds for better climate prediction and resilience.
![Hydrologist Jesus Gomez-Velez brings his expertise in river systems and mathematics to ORNL’s modeling and simulation research to better understand flow and transport processes in the nation’s watersheds. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-02/2023-P00555_0_0.jpg?h=b69e0e0e&itok=Fw7O0Wtq)
Hydrologist Jesús “Chucho” Gomez-Velez is in the right place at the right time with the right tools and colleagues to explain how the smallest processes within river corridors can have a tremendous impact on large-scale ecosystems.