David Silberberg is a principal professional staff member at the Johns Hopkins University Applied Physics Laboratory (APL) and is the research director of the Johns Hopkins Institute for Assured Autonomy. He is the chair of the Information Systems Engineering program at the Johns Hopkins Whiting School of Engineering. He has conducted extensive research and development in the areas of leading-edge AI and machine learning algorithms, including graph analytics, distributed and large-scale architectures, intelligent access to distributed and heterogeneous database systems, and semantic graph query languages. Silberberg led the Large Scale Analytics group at the APL that applies machine learning and AI-base algorithms to perform descriptive, predictive, and prescriptive analytics on large and complex data. He also served as chief architect for the deep archive of NASA mission data and for the Hubble Space Telescope data archive. Silberberg received bachelor’s and master’s degrees in Computer Science from the Massachusetts Institute of Technology and a PhD in Computer Science from the University of Maryland, College Park. He teaches a computer science graduate course on large-scale database systems at Johns Hopkins University’s Engineering for Professionals program.