About Me

As a child, I became obsessed with the ridiculous dream of building robots after watching science fiction movies. That harmless gimmick eventually dragged me deep into the labyrinth of Robotics, Automation, and Artificial Intelligence. After sacrificing some of the most valuable years of my life at Yeungnam University to capture the elusive golden deer called a Ph.D., I now find myself pursuing a research career that supposedly aims to save the world through intelligent systems. My so-called academic journey in South Korea has essentially been a peculiar struggle for survival. I came here on a Korean Government Scholarship, only to become trapped in the relentless machinery of Control Engineering, with no obvious escape route left. My master’s research carried the impressive title: “Autonomous Motion Control of Mobile Robot Using Robot Operating System.” In reality, the work involved teaching an omnidirectional robot to navigate through a dynamic industrial environment without crashing into anything, using ROS, LiDAR, and IMU data. That experience pushed me toward even deeper and more painfully complex research in industrial systems. My Ph.D. dissertation was titled “A Study on Machine Learning-Based Control and Fault Detection Methods in Roll-to-Roll Manufacturing Systems.” Instead of relying on conventional mathematical models, I developed an integrated data-driven framework that combined Model-Free Adaptive Control (MFAC) for robust tension regulation with Gaussian Process Regression (GPR) for uncertainty-aware fault detection. By leveraging real-time I/O data, the system was designed to continuously adapt to changing conditions. Experimental results demonstrated tension regulation within ±0.02 N and the ability to detect critical faults in under 100 milliseconds, all without generating false alarms. The long-term goal of my otherwise monotonous academic life is to develop intelligent industrial machinery capable of performing complex tasks while operating safely and seamlessly alongside humans in human-centered environments. For now, I remain determined to keep this academic drama alive indefinitely by researching reinforcement learning-based controllers, AI-driven fault detection techniques, and other suitably grand-sounding topics, all in the name of advancing complex autonomous systems.