Dylan Asmar is a researcher and engineer working at the intersection of decision making under uncertainty, multiagent autonomy, and human-AI collaboration. He is currently a member of the technical staff at MIT Lincoln Laboratory, where he develops algorithms for autonomous systems operating in complex and uncertain environments.

Dylan received his Ph.D. in Aeronautics and Astronautics from Stanford University, where he worked with Professor Mykel J. Kochenderfer in the Stanford Intelligent Systems Laboratory. His doctoral research focused on efficient multiagent planning, including methods that allow agents to communicate implicitly through shared action suggestions. This work is motivated by a broader interest in combining human expertise with algorithmic decision-making to support effective human-autonomy teaming.

Before Stanford, Dylan served as an F-22 Operational Test and Evaluation Pilot in the United States Air Force, where he worked on flight test, evaluation, and data-driven modernization efforts for advanced aircraft systems. He continues to serve part-time in that role with the Nevada Air National Guard.

Dylan holds a Master of Science in Aeronautics and Astronautics from the Massachusetts Institute of Technology, where his research on airborne collision avoidance in mixed-equipage environments contributed to the development of the Airborne Collision Avoidance System X (ACAS X). He graduated as a Distinguished Graduate from the United States Air Force Academy with a Bachelor of Science in Mathematics and Astronautical Engineering, earning honors for both Academic and Military Distinction.

Dylan has also been active in teaching and mentorship, including serving as Head Teaching Assistant for Stanford graduate courses in Decision Making Under Uncertainty (AA228/CS238) and Engineering Design Optimization (AA222/CS361). His work is shaped by both research and operational experience, with the goal of developing collaborative autonomous systems that enhance, rather than replace, human judgment.