Personal profile
Research Interests
- Embedded Real-Time Systems
- Edge AI Solutions
- Industrial Automation
Education/Academic qualification
PhD, Seoul National University (SNU)
Mar 1996 → Aug 2001
Master, Seoul National University (SNU)
Mar 1994 → Feb 1996
Bachelor, Seoul National University (SNU)
Mar 1990 → Feb 1994
Expertise related to UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):
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SDG 9 Industry, Innovation, and Infrastructure -
SDG 11 Sustainable Cities and Communities
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Dive into the research topics where Taehyoun Kim is active. These topic labels come from the works of this person. Together they form a unique fingerprint.
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Collaborations and top research areas from the last five years
Recent external collaboration on country/territory level. Dive into details by clicking on the dots or
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Hybrid Approach for Machine Anomaly Detection Across Diverse Operating Conditions: Combining Self-Supervised Learning With Vibration Statistics
Lee, S. & Kim, T., 2025, In: IEEE Transactions on Instrumentation and Measurement. 74, 3540215.Research output: Contribution to journal › Article › peer-review
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FRFconv-TDSNet: Lightweight, Noise-Robust Convolutional Neural Network Leveraging Full-Receptive-Field Convolution and Time-Domain Statistics for Intelligent Machine Fault Diagnosis
Lee, S. & Kim, T., 26 Aug 2024, In: IEEE Transactions on Instrumentation and Measurement. 73, p. 1 13 p., 3528213.Research output: Contribution to journal › Article › peer-review
8 Scopus citations -
Multi-domain vibration dataset with various bearing types under compound machine fault scenarios
Lee, S., Kim, T. & Kim, T., Dec 2024, In: Data in Brief. 57, 110940.Research output: Contribution to journal › Article › peer-review
Open Access9 Scopus citations -
Impact of Deep Learning Optimizers and Hyperparameter Tuning on the Performance of Bearing Fault Diagnosis
Lee, S. & Kim, T., 2023, In: IEEE Access. 11, p. 55046-55070 25 p.Research output: Contribution to journal › Article › peer-review
Open Access19 Scopus citations -
Urban Noise Analysis and Emergency Detection System using Lightweight End-to-End Convolutional Neural Network
Park, J., Yoo, T., Lee, S. & Kim, T., Oct 2023, In: International Journal of Computers, Communications and Control. 18, 5, 5814.Research output: Contribution to journal › Article › peer-review
Open Access7 Scopus citations