Artificial Intelligence

Dave Barsic is an Assistant Program Manager in the Force Projection Sector at JHU/APL. He is a member of the JHU/APL Principal Professional Staff and has 19 years of experience focusing on machine learning and signal processing applications for various U.S. Navy efforts.
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David Handelman is a Senior Roboticist at the Johns Hopkins University Applied Physics Laboratory. He is a member of the Robotics Group in the Research and Exploratory Development Department. His current research focus is adaptive human-robot teaming based on the emulation of human skill acquisition by robots using neuro-symbolic AI/ML.
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Dr. Christopher Ratto is a member of the Senior Professional Staff at The Johns Hopkins University Applied Physics Laboratory.
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Dr. Jane Pinelis is the Chief of the Test, Evaluation, and Assessment branch at the Department of Defense Joint Artificial Intelligence Center (JAIC). She leads a diverse team of testers and analysts in rigorous test and evaluation (T&E) for JAIC capabilities, as well as development of T&E-specific products and standards that will support testing of AI-enabled systems across the DoD.
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Will Gray-Roncal is a Principal Research Scientist at the Johns Hopkins University Applied Physics Laboratory, with expertise in data science, neuroscience, artificial intelligence, precision medicine, and learning research, including leadership of the CIRCUIT Program.
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Dan Yaroslaski is a senior professional staff member in the Tactical Intelligence Systems group within the Asymmetrical Operations Sector at Johns Hopkins Applied Physics Laboratory.
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Reed Young is a member of the senior professional staff in the Research and Exploratory Development Mission Area at JHU/APL, where he serves as the program manager for Robotics and Autonomy.
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Adam Watkins is a principal staff member of JHU/APL with over 15 years’ experience in autonomy and robotics.
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Tamim Sookoor is a researcher at JHU/APL, where his research interests include cyber physical systems (CPS), cyber security, the Internet of Things (IoT), and machine learning.
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Christina Selby is a senior professional staff member and section supervisor at JHU/APL, with expertise in developing and analyzing mathematical methodologies to solve critical problems that are not well understood.
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