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Media Contacts
Shih-Chieh Kao, manager of the Water Power program at ORNL, has been named a fellow of the American Society of Civil Engineer’s Environmental & Water Resources Institute, or EWRI.
Colleen Iversen, ecosystem ecologist, group leader and distinguished staff scientist, has been named director of the Next-Generation Ecosystem Experiments Arctic, or NGEE Arctic, a multi-institutional project studying permafrost thaw and other climate-related processes in Alaska.
Computing pioneer Jack Dongarra has been elected to the National Academy of Sciences in recognition of his distinguished and continuing achievements in original research.
Xiao Wang, a research scientist at ORNL, has been named a senior member of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals. Wang works in the lab’s Computing and Computational Sciences Directorate’s Advanced Computing for Health Sciences Section.
Craig Blue, Defense Manufacturing Program Director at the Department of Energy’s Oak Ridge National Laboratory, was recently elected to a two-year term on the Institute for Advanced Composites Manufacturing Innovation Consortium Council, a body of professionals from academia, state governments, and national laboratories that provides strategic direction and oversight to IACMI.
Mickey Wade has been named associate laboratory director for the Fusion and Fission Energy and Science Directorate at the Department of Energy’s Oak Ridge National Laboratory, effective April 1.
A partnership of ORNL, the Tennessee Department of Economic and Community Development, the Community Reuse Organization of East Tennessee and TVA that aims to attract nuclear energy-related firms to Oak Ridge has been recognized with a state and local economic development award from the Federal Laboratory Consortium.
Merlin Theodore is one of eight new board members announced by President Biden; she will join the 25-member board for a six-year term.
Scientists at the Department of Energy’s Oak Ridge National Laboratory are leading a new project to ensure that the fastest supercomputers can keep up with big data from high energy physics research.
A new deep-learning framework developed at ORNL is speeding up the process of inspecting additively manufactured metal parts using X-ray computed tomography, or CT, while increasing the accuracy of the results. The reduced costs for time, labor, maintenance and energy are expected to accelerate expansion of additive manufacturing, or 3D printing.