Past Event: Oden Institute Seminar

Perspectives on Artificial Intelligence and Machine Learning for Cyberphysical Systems in the Department of Defense

Matthew Clark, Galois, Inc.

Abstract

With the continued rise in the interest of Machine Learning and AI technologies for DoD applications, this talk will briefly cover my perspective on the terms Autonomy, AI, Machine Learning as they relate to future DoD opportunities. The perspective will start from the "Three Waves of AI" discussion by John Launchbury while he was the DARPA I2O director. From that perspective, this talk will briefly cover the up and coming challenges, research opportunities and some particular agencies and industry partners that plan on increasing their investment in AI significantly over the next 5 years. Bio At Galois, Mr. Clark focuses on the design and assurance of intelligent cyber-physical systems. His research interests lie in first-principles approaches to the development of hybrid systems, artificial intelligence, fuzzy logic, run-time assurance protected systems, robotics and control. Before joining Galois, Mr. Clark was previously the lead for Autonomous Manned-Unmanned Teaming for the Aerospace Systems Directorate, Air Force Research Laboratory (AFRL). During his tenure at AFRL, Mr. Clark also served as the supervisor of the Autonomous Controls Branch, Power and Control Division, Aerospace Systems Directorate, where he received the Air Force Meritorious Civilian Service Award. Prior to that he was the Technical Area Lead for the verification and validation of complex and autonomous systems. He led a team of in-house researchers in the design, analysis, verification, and validation of autonomous control systems. He was also considered the primary subject matter expert for AFRL Test and Evaluation, Verification and Validation (TEV&V) of complex systems and the DoD co-leader and primary author of the Test and Evaluation Strategy for the Assistant to the Secretary of Defense, Research and Evaluation, Autonomy Community of Interest, (ASD/R&E COI).