Confesor Santiago is the Chief for the Systems Modeling and Optimization Branch in the Aviation Systems Division at NASA Ames Research Center. Before taking on branch chief duties, he was the Technical Lead for the Detect and Avoid Modeling and Simulation Team within the Unmanned Aircraft Systems (UAS) Integration in the National Airspace System (NAS) Project. Before joining NASA in 2011, he worked as a Computer Scientist at the Federal Aviation Administration working on various NextGen projects. He holds a Bachelor's and Master’s degree in Computer Science from Rowan University. His work has included air traffic trajectory prediction accuracy, conflict detection and resolution, software development, simulation and modeling of air traffic management systems, and UAS detect and avoid.
Mr. Santiago has authored or co-authored more than 20 technical conference publications, four journal articles, and holds a U.S. patent. Recently, he has conducted research supporting the development of minimum operational performance standards (MOPS) for UAS detect and avoid systems through RTCA Special Committee 228. The DAA MOPS (i.e., DO-365) put technical standards on the performance of UAS DAA systems to safely and efficiently operate in the NAS.
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