Yong Chae Kim

Yong Chae Kim

Ph.D. Candidate · Mechanical Engineering · Seoul National University

My research focuses on deep learning for Prognostics and Health Management (PHM) in mechanical systems, including fault diagnosis, signal generation, and denoising. I work with domain adaptation, diffusion models, and physics-informed approaches. Currently, I am exploring manufacturing foundation models and agentic AI for industrial applications.

Outside of research, I enjoy traveling to new places, working on meaningful projects, and connecting with people.

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Selected Publications

Representative first-author journal articles. Full list on CV page →

Physics-guided deep ensemble learning for the remaining useful life prediction of machine tools using kernel density estimation

Kim, Y.C., Kim, B., Kim, M., Lee, S.K., Jung, J.H., & Youn, B.D.

Int'l J. Precision Eng. and Manufacturing-Green Technology 2025 SCIE

Latent Space Alignment based Domain Adaptation (LSADA) for Fault Diagnosis of Rotating Machinery

Kim, Y.C., Ko, J.U., Lee, J., Kim, T., Jung, J.H., & Youn, B.D.

Advanced Engineering Informatics 2024 SCIE

Gradient Alignment based Partial Domain Adaptation (GAPDA) using a domain knowledge filter for fault diagnosis of bearing

Kim, Y.C., Lee, J., Kim, T., Baek, J., Ko, J.U., Jung, J.H., & Youn, B.D.

Reliability Engineering & System Safety 2024 SCIE

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Research Overview

Program

Data Drift Management

Selected Publications

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