Luis Alvarez is a nationally recognized technical leader in aviation autonomy, artificial intelligence for airspace safety, and the development of next-generation airborne systems. As Technical Lead for Aviation Autonomy and AI Safety at MIT Lincoln Laboratory, Luis has spearheaded foundational work in collision avoidance, contingency management, and drone swarm coordination for both commercial and defense aviation domains.
Luis served as a principal artificial intelligence lead of ACAS X, a new generation of AI-enabled airborne collision avoidance systems, advancing them from concept to field-tested implementation and international standardization. His leadership was instrumental in the use of deep reinforcement learning (DRL) to improve self-separation, real-time risk mitigation, and detect-and-avoid strategies for both traditional and advanced air mobility (AAM) platforms. Luis led the design and flight demonstration of distributed drone behaviors—including vision-based pursuit, autonomous 3D search using belief maps, and radar-integrated guidance—all of which are critical to modern counter-UAS and homeland defense missions.
He has published extensively on the optimization of DRL-based control policies for safety-critical systems. His algorithms have enabled unmanned aircraft to dynamically avoid population centers during emergencies, to execute safe landings under uncertainty, and to operate with high sample efficiency at scale.
He is a recipient of two R&D 100 Awards, a finalist for the Collier Trophy, and was selected by the National Academy of Engineering as one of the top 100 emerging engineering leaders. Luis was also honored with the AIAA New England Young Professional Award for his impact on aerospace innovation. He holds an S.M. in Aeronautics and Astronautics from MIT and dual B.S. degrees in Aerospace and Mechanical Engineering from the University of Florida.