• Developed and implemented advanced algorithms for cross-domain autonomy in maritime environments, integrating Unmanned Surface Vehicles (USVs) and Unmanned Aerial Vehicles (UAVs) to execute complex missions with minimal operator input.• Enabled autonomous swarm behaviors for diverse fleets, allowing large-scale heterogeneous vehicles to meet operator-defined objectives in fully autonomous settings.• Supported field test events, deploying autonomy across multiple vehicle types, and interfaced directly with operators and customers to ensure mission success.• Created formation control and obstacle avoidance algorithms for vehicle swarms in contested and dynamic environments, enhancing operational effectiveness and adaptability.

• Driving the integration of future autonomy onto the Boeing 777X, optimizing architecture for fully autonomous operation and multiple pilot configurations, with a hands-on, learn-by-doing approach.• Developing Autonomous Continued Safe Flight and Landing (ACSFL) systems, implementing a prototype to recommend enhancements for Boeing's next commercial aircraft with extended autonomous capabilities. Applying expertise in RSLQR, optimal control, and non-linear control.• Leading successful customer demonstrations in Boeing's high-fidelity simulation, showcasing fully autonomous landings, including runway exit.• Implementing a proactive approach in recommending aircraft architecture changes to provision the next commercial airplane for enhanced autonomy capabilities.• Innovating safety analysis processes, ensuring ACSFL's safety parity or superiority to piloted aircraft.

• Conducted rapid prototyping of Lighter-Than-Air Vehicles (LTAV), emphasizing controllability,maneuverability, and the integration of hardware for swarm technology.• Developed a fully custom autonomy suite using ROS, enabling seamless autonomous operation and real-time diagnostics reporting to the ground station.• Designed and trained computer vision systems for autonomous LTAVs, identifying targets,adversaries, and goals in GPS-denied environments. Created advanced autonomous routines based on computer vision and employed open-source visual-inertial odometry for local positioning and waypoint navigation.• Constructed robust and adaptive control systems for advanced autonomous UAV routines. Implemented a cascaded Neural Network Model Reference Adaptive Control (NN MRAC) controller to handle modeling and disturbance uncertainties in dynamic environments.• Executed least-squares system identification with sparse Bayesian regression of error dynamics on LTAVs, establishing an accurate non-linear model for the airship.• Engineered a custom hardware suite utilizing a Raspberry Pi, Intel RealSense camera, and FPV drone motors to build the LTAVs. Integrated autonomous scoring capability into the LTAVs, allowing it to save the location of game goals and autonomously score without pilot intervention.

• Led design, development, and testing of cost-effective rotary-wing unmanned aircraft systems (UAS) for high-volume production. UAV components were optimized for superior range and payload capacity through extensive research and diverse material testing.• In-house construction of custom drone frames using materials from cardboard to carbon fiber. Tested Y4 to X8 copter configurations for performance optimization.• Tested a variety of flight controllers and electronics, primarily utilizing a Pixhawk running ArduPilot and Mission Planner.• Enhanced flight endurance through autonomous field testing, refining overall system performance.