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Media Contacts
![Ryan Kerekes is leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory. Photos by Genevieve Martin, ORNL. Ryan Kerekes is leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory. Photos by Genevieve Martin, ORNL.](/sites/default/files/styles/list_page_thumbnail/public/Ryan%20Kerekes%20Profile%20lab1_0.jpg?itok=btnfhbaJ)
As leader of the RF, Communications, and Cyber-Physical Security Group at Oak Ridge National Laboratory, Kerekes heads an accelerated lab-directed research program to build virtual models of critical infrastructure systems like the power grid that can be used to develop ways to detect and repel cyber-intrusion and to make the network resilient when disruption occurs.
![The sensors measure parameters like temperature, chemicals and electric grid elements for industrial and electrical applications. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy The sensors measure parameters like temperature, chemicals and electric grid elements for industrial and electrical applications. Credit: Carlos Jones/Oak Ridge National Laboratory, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/drone%20inspecting%20EPB%20pole%20mounted%20transformers.jpg?itok=CiRIK4cC)
Brixon, Inc., has exclusively licensed a multiparameter sensor technology from the Department of Energy’s Oak Ridge National Laboratory. The integrated platform uses various sensors that measure physical and environmental parameters and respond to standard security applications.
For the past six years, some 140 scientists from five institutions have traveled to the Arctic Circle and beyond to gather field data as part of the Department of Energy-sponsored NGEE Arctic project. This article gives insight into how scientists gather the measurements that inform t...
![ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system. ORNL’s Steven Young (left) and Travis Johnston used Titan to prove the design and training of deep learning networks could be greatly accelerated with a capable computing system.](/sites/default/files/styles/list_page_thumbnail/public/news/images/RAvENNA%20release%20pic.png?itok=2bDpK5Mo)
A team of researchers from the Department of Energy’s Oak Ridge National Laboratory has married artificial intelligence and high-performance computing to achieve a peak speed of 20 petaflops in the generation and training of deep learning networks on the
![Default image of ORNL entry sign](/sites/default/files/styles/list_page_thumbnail/public/2023-09/default-thumbnail.jpg?h=553c93cc&itok=N_Kd1DVR)
Scientists of the Next-Generation Ecosystem Experiments are blogging from the Arctic this summer. Follow their adventures at http://ngee-arctic.blogspot.com/. Participants share troubles and triumphs from the field in entries with headings like "Flying Wild Alaska" and "Hitting the Tundra." "The b...