Barry Daniel
About Barry Daniel
Barry Daniel serves as Senior R&D Staff at Oak Ridge National Laboratory, where he has worked since 2005. He is recognized for his expertise in radar and optics, having developed methodologies for LIDAR data conversion and the use of NEXRAD radars in machine learning applications.
Work at Oak Ridge National Laboratory
Barry Daniel has been employed at Oak Ridge National Laboratory since 2005, serving as Senior R&D Staff for 19 years. In this role, he has contributed to significant advancements in radar and optics technologies. His work includes developing methodologies for utilizing NEXRAD weather radars to detect and characterize non-meteorological plumes through machine learning techniques. This innovative approach has enhanced the understanding of radar applications in various contexts.
Education and Expertise
Barry Daniel holds multiple degrees in engineering and computer science. He earned a Bachelor of Science in Electrical, Electronics and Communications Engineering from Tennessee Technological University, completing his studies from 1988 to 1995. He furthered his education with a Master of Science in Electrical, Electronics and Communications Engineering from the University of Alabama in Huntsville between 1998 and 2000. He achieved a Doctor of Philosophy in Electrical and Electronics Engineering from Tennessee Technological University from 2015 to 2020. His educational background supports his expertise in radar and optics.
Previous Experience at Dynetics, Inc.
Before joining Oak Ridge National Laboratory, Barry Daniel worked at Dynetics, Inc. from 1996 to 2005 as Senior Engineer and Branch Manager. During his nine years there, he led the development of real-time radar environment models. These models supported the injection of simulated radar signals into the processing chain of multiple counter-fire radars, showcasing his leadership and technical skills in radar technology.
Methodologies and Innovations
Barry Daniel has created several methodologies that have advanced the field of radar technology. Notably, he developed a methodology for converting LIDAR point cloud data into CAD drawings specifically for nuclear test setup documentation. Additionally, he restructured an RF clutter simulation based on the interim Billingsley clutter model, enabling its real-time execution on GPU hardware. These contributions reflect his innovative approach to solving complex engineering challenges.
Recognition in the Radar Community
Barry Daniel is recognized as a subject matter expert in radar and optics, particularly among Army customers. He has established a national reputation as an unbiased and innovative problem solver within the radar community. His expertise and contributions have positioned him as a valuable resource in addressing radar-related challenges.