As an active-duty U.S. Coast Guard officer and seasoned MH-65 helicopter pilot with over 2,300 flight hours, Eric Schwartz is no stranger to high-stakes missions and complex aviation systems. That frontline experience inspired his capstone project in the Systems Engineering graduate program at Johns Hopkins Engineering for Professionals (EP), where he explored how unmanned aerial systems could support the Coast Guard’s core mission of search and rescue.
The project, titled the Autonomous Maritime Search and Rescue Unmanned Aerial Vehicle (AMSUAV), applies systems engineering principles to design an unmanned aerial vehicle tailored for maritime search and rescue operations.
“The idea was to fuse current long-range UAS with advanced AI algorithms to analyze sensor data in real time,” said Schwartz, a systems manager for the C-27J aircraft for the U.S. Coast Guard’s Medium Range Surveillance program. “This could increase the speed and accuracy of search operations while reducing the cognitive load on human operators.”
His system integrates long-range unmanned aerial systems with advanced AI algorithms to process visual and sensor data in real time, improving mission accuracy. By automating data analysis, AMSUAV would reduce human operators’ cognitive load. Schwartz’s conceptual design also includes the UAV’s capability to deliver rescue payloads, like life rafts or radios, to distressed mariners.
The project aimed to demonstrate the feasibility of such a system through a rigorous application of systems engineering methodologies, including requirements analysis, functional architecture, and model-based systems engineering (MBSE) using Catia Magic, he said.
“The iterative SE process, requirements analysis, functional definition, physical definition, and design validation were foundational to my approach,” Schwartz explained.
He faced a number of technical challenges during his capstone, including defining AI/ML performance requirements and building a modular functional architecture. Limited familiarity with AI/ML meant additional research, while functional coupling issues prompted an important realization about the tradeoffs of complexity and clarity in single-person projects.
“One lesson I had to accept was that as a one-person team, I simply couldn’t capture the full complexity of the system. It became a valuable learning point in scope management,” he said.
Schwartz noted that he benefited from faculty who encouraged students to start thinking about their capstone early and helped him build confidence with MBSE tools well before project work began. Among the most influential courses was Advanced Concepts in Agile Technical Management, which Schwartz credits with helping him internalize key principles of modern system development, despite it being the most demanding course he took.
“The rigor of that course really paid off,” he noted. “I now feel confident applying agile development methods in Coast Guard acquisitions, which have traditionally relied on waterfall models.”
After completing the program, Schwartz was assigned to Coast Guard Headquarters in Washington, D.C., where he oversees both the aircraft and the logistics systems that sustain them—an area where he says his training in systems thinking and lifecycle management is proving invaluable.
His advice to future students? Embrace MBSE tools early, choose synchronous classes when possible, and accept that your capstone won’t be perfect—but it will be meaningful.
“You’re a one-person team. Keep it manageable, learn from mistakes, and focus on applying systems engineering principles. That’s where the real value lies,” he said.