Research

My research integrates systems engineering, complexity science, design methodology, and space systems. I develop quantitative methods to represent, analyze, and manage the complexity of engineering systems and their design processes.

Current Research — MIT (2023–Present)

• Complexity quantification and budgeting for engineering systems using graph-based abstraction
• Systems engineering theories and system-probing methods
• Design structure matrix analysis, spectral clustering, and controlled system decomposition
• Optimal design sequences for multidisciplinary analysis and optimization
• Visibility analysis and upper bounds for uncatalogued resident space objects using in-situ optical sensor constellations
• Space situational awareness and marketplace architecture

Previous Research — KAIST (2022–2023)

• Trajectory optimization and sequential convex optimization
• Development of in-house quadratic programming and second-order cone programming solvers

Previous Research — Satrec Initiative (2019–2022)

• Satellite attitude determination and control for Earth-observation missions
• Quaternion guidance with rate constraints
• Non-iterative attitude guidance on geodesic lines
• High-precision satellite attitude and misalignment estimation
• Onboard flight-control software development, testing, verification, and validation

Previous Research — KAIST (2017–2019)

• Sequential convex programming for real-time guidance
• Trajectory optimization of aerodynamically controlled vehicles
• Impact-time and impact-angle control guidance
• Mixed-integer linear programming for optimal weapon-target assignment
• Bearings-only target tracking and angle-only estimation filters