For this seminar, Dr. Fossaceca will explore some of the motivating factors behind US Army Research in AI and ML and provide a survey of a subset of the US Army Research Laboratory’s (ARL) Computational and Information Sciences Directorate’s (CISD) recent research in online, nonparametric learning that quickly adapts to variable underlying distributions in sparse exemplar environments, as well as a technique for unsupervised semantic scene labeling that continuously learns and adapts semantic models discovered within a data stream. We also look at a newly developed algorithm that leverages human input to help intelligent agents learn more rapidly and a novel research study working to discover foundational knowledge that is required for human and robots to communicate via natural language. Finally, Dr. Fossaceca will discuss a method for finding chains of reasoning with incomplete information, using semantic vectors. The specific research exemplars provide approaches for overcoming the specific shortcomings of commercial AI and ML methods as well as the brittleness of current commercial techniques such that these methods can be enhanced and adapted so as to be applicable to army relevant scenarios.
Dr. Fossaceca is the Associate Division Chief for the US Army Research Laboratory’s Information Sciences Division, where he supports basic research programs in machine learning and artificial intelligence related to autonomous systems, situational understanding and battlefield information processing, and is project manager for ARL’s Intelligent Systems Center. Prior to joining ARL, Dr. Fossaceca worked for 30 years at several DoD and Telecommunications companies in numerous leadership roles including Principal Investigator on several Small Business Innovation Research (SBIR) programs for the US Navy at Ultra Electronics, 3eTI, Engineering Director at AT&T/Lucent/Bell Labs for Next Generation Telecommunications Systems and Engineering Vice President for modernization of the US Army’s satellite-based Blue Force tracking system at Comtech Telecommunications. Dr. Fossaceca has conducted research and development in adaptive signal processing, machine learning in data constrained environments, network intrusion detection, and the internet of battlefield things. Dr. Fossaceca is co-inventor on six patents related to wireless communications and signal detection and serves as a reviewer for several refereed journals.
Dr. Fossaceca hold Bachelor’s and Master’s degrees in Electrical Engineering from Manhattan College and Syracuse University respectively, an MBA from Virginia Tech and a Ph. D. in Systems Engineering from George Washington University.