Jayden Dongwoo Lee
Postdoctoral Researcher (AITA InnoCORE), Ph.D. · Dept. of Aerospace Engineering, KAIST
N27 Building, Room 4117
KAIST, 291 Daehak-ro, Yuseong-gu
Daejeon 34141, Republic of Korea
cin6474@kaist.ac.kr
I am a postdoctoral researcher in the AITA InnoCORE program, Department of Aerospace Engineering at KAIST, where I completed my Ph.D. under Prof. Hyochoong Bang — a dissertation honored with the KAIST College of Engineering Best Dissertation Award (2026). My work lives on the seam between data-driven methods and flight control — I design the estimators and controllers that keep aircraft flying when something goes wrong, and I care about taking them from theory all the way onto real flight hardware.
A large part of my research develops data-driven modeling and control. Using sparse identification (SINDy), the Koopman operator, and Gaussian-process methods, I learn vehicle dynamics from data and turn them into disturbance observers, model-predictive controllers, and adaptive laws. I apply these tools to fault detection, diagnosis, and fault-tolerant control for multirotors, eVTOL, and urban air mobility — systems where losing an actuator mid-flight is not an option.
More recently I work on navigation in GNSS-denied environments. When satellite signals are jammed or simply gone, a vehicle still has to answer one question: where am I? I fuse quantum magnetometers and magnetic-anomaly maps through factor graph optimization so aircraft can localize themselves without GPS — work that connects my control background to real quantum-sensing hardware.
Across all of this I try to close the loop between algorithm and airframe: redundant flight-control computers, hardware-in-the-loop testing, and flight campaigns on platforms from quadrotors to hoverbikes. I earned my B.S. at UNIST and my M.S. and Ph.D. at KAIST, with two years in between as a control engineer in industry.
I have authored 21 international journal articles and more than 70 conference papers, hold 5 patents, and have received over ten best-paper awards. You can read more about my work on the research and publications pages, or my full CV. I’m always glad to hear from people working on hard estimation, control, and navigation problems — feel free to reach out.
news
| May 20, 2026 | Presented Factor Graph Optimization-Based Magnetic Navigation Using a Quantum Magnetometer at the IPNT 2026 conference in Seoul. |
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| May 01, 2025 | Received the Best Paper Award from the Korea Institute of Military Science and Technology (KIMST). |
| Mar 15, 2025 | Awarded the Jo Jung-Hoon Scholarship, Dept. of Aerospace Engineering, KAIST. |
| Dec 01, 2024 | Won the Excellence Award (Minister of Science and ICT Award) at the K-Startup Grand Championship, and 1st place at the DAPA Defense Technology Startup Competition. |
selected publications
- IPNT
- IEEE SensorsSensor and Actuator Fault Detection and Isolation for Urban Air MobilityIEEE Sensors Journal, 2026
- Sparse Identification of Nonlinear Dynamics-based Model Predictive Control for Multirotor Collision AvoidanceIET Control Theory & Applications, 2025
- ASTSparse Online Gaussian Process Regression-based Robust Nonlinear Dynamics Inversion for Multirotor with Forward Flight Ground EffectAerospace Science and Technology, 2025
- CEPPractical Fault-Tolerant Control Allocation based on Attainable Control Set Analysis for a Coaxial DodecacopterControl Engineering Practice, 2025
- IMechE GFeedback Linearization-based Model Reference Adaptive Control for Multirotor UAVs under Uncertainties from Fuel and PayloadProceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 2025
- IJCASData-driven Fault Diagnosis of Nonlinear Systems with Parameter Uncertainty using Deep Koopman Operator and Weighted Window Extended Dynamic Mode DecompositionInternational Journal of Control, Automation, and Systems, 2024
- Data-driven Fault Detection and Isolation for Multirotor System using Koopman OperatorJournal of Intelligent & Robotic Systems, 2024
- IJASSFault-tolerant Control for Aircraft with Structural Damage using Sparse Online Gaussian Process RegressionInternational Journal of Aeronautical and Space Sciences, 2024