Dr. Jeonghoon Moon | Power Electronics | Best Researcher Award

Dr. Jeonghoon Moon | Visiting Professor in the Department of Electronic Engineer | Chosun University | South Korea

Jeonghoon Moon is a distinguished researcher in power electronics and AI-based control, with a focus on EMI-aware predictive control of DC–DC converters, sensor-level CPS security, and battery balancing strategies. His research integrates advanced machine learning techniques, including physics-informed LSTM models, with practical hardware implementations on DSP platforms for real-time disturbance prediction, ripple reduction, and system stability. He has made significant contributions to predictive and robust control, developing lightweight controllers that approximate LSTM outputs for deterministic execution on embedded systems, enabling faster detection latency and improved DC-rail performance. Moon has proposed novel safety envelopes unifying efficiency deviation with time- and frequency-domain ripple metrics to guide safe derating under dynamic operating conditions and potential spoofing scenarios. His work also encompasses EMI-aware PWM shaping and battery module balancing, validated through rigorous MATLAB/Simulink simulations and reproducible hardware experiments. Moon maintains multi-institutional collaborations with academic and industry partners to advance power electronics and AI integration. His research outputs include four SCI/SCIE journal publications, multiple consultancy projects, and one patent, reflecting both academic rigor and industrial relevance. His research impact is evidenced by 25 Scopus-indexed documents with 25 citations and an h-index of 2. Moon’s contributions extend to ultrasonic piezo resonance tracking and high-speed resonant frequency detection using AI-guided methodologies, demonstrating the applicability of machine learning in real-time control systems and intelligent energy management.

Publication Profile

Scopus | ORCID

Featured Publications

Moon, J.-H., Kim, J.-H., & Lee, J.-H. (2025). Sensor-Level Anomaly Detection in DC–DC Buck Converters with a Physics-Informed LSTM: DSP-Based Validation of Detection and a Simulation Study of CI-Guided Deception. Applied Sciences.

Moon, J., Lim, S., Kim, J., Kang, G., & Kim, B. (2024). A Study on the Mechanical Resonance Frequency of a Piezo Element: Analysis of Resonance Characteristics and Frequency Estimation Using a Long Short-Term Memory Model. Applied Sciences.

Moon, J., Park, S., & Lim, S. (2022). A Novel High-Speed Resonant Frequency Tracking Method Using Transient Characteristics in a Piezoelectric Transducer. Sensors.

Moon, J. H. (2021). A Study on Resonance Tracking Method of Ultrasonic Welding Machine Inverter. Journal of the Korean Society of Industry Convergence.

Moon, J. H. (2021). Fast and Stable Synchronization Between the Grid and Generator by Virtual Coordinates and Feed-Forward Compensation in Grid-Tied Uninterruptible Power Supply System. IEEE Access.