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GwanPil Kim: Difference between revisions
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==Education== | ==Education== | ||
* | * March. 2025 – Present: Computer Science and Engineering, Chung-Ang University | ||
** | ** Ph.D, Degree in BigData, Seoul, South Korea | ||
* March 2022 –March 2024: Computer Science and Engineering, Chung-Ang University | |||
** M.S. Degree in BigData, Seoul, South Korea | |||
==Research Interests== | ==Research Interests== | ||
* Machine Learning / Deep Learning | * Machine Learning / Deep Learning | ||
* Graph Embedding | * Graph Embedding | ||
* | * Remaining Useful Life(RUL) Prediction | ||
==Research Experience== | |||
==Journal Publications== | ==Journal Publications== | ||
* '''Gwanpil Kim''', et al. "Fuzzy particle filtering based approach for battery RUL prediction with uncertainty reduction strategies." Expert Systems 42.4 (2025): e70027. | |||
* '''Gwanpil Kim''', Jason J. Jung, and David Camacho. "Health indicator construction based on normal states through FFT‐graph embedding." Expert Systems 41.11 (2024): e13689. | |||
==Conference papers== | |||
* '''Gwanpil Kim''', and Jason J. Jung. "VQ-GCAE: Vector-Quantized Graph Convolutional Autoencoder for Early Anomaly Detection in Multivariate Time Series." International Conference on Intelligent Data Engineering and Automated Learning. Cham: Springer Nature Switzerland, 2025. | |||
==Teaching== | |||
* Teaching Assistant, Class for practicing of Business intelligence, 2023 Fall, graduate course, Department of Computer Science and Engineering, Chung-Ang University, Seoul, South Korea. | |||
* Teaching Assistant, Class for practicing of knowledge graph, 2023 Spring, graduate course, Department of Computer Science and Engineering, Chung-Ang University, Seoul, South Korea. | |||