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 | |||
* Graph Embedding | |||
* Remaining Useful Life(RUL) Prediction | |||
==Research Experience== | ==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. | |||
Latest revision as of 18:28, 5 March 2026
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
- Machine Learning / Deep Learning
- Graph Embedding
- Remaining Useful Life(RUL) Prediction
Research Experience
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.