Min-Seung Ko

The University of Texas at Austin — United States

Engineering · Physical Sciences

6h-index407citations20works0.52yr avg
OpenAlex↗ORCID↗Google Scholar↗Lab page↗

Accepting Students?

No reports yet. Know if this professor is taking students?

Research Topics

Machine Fault Diagnosis Techniques(4), Fault Detection and Control Systems(4), Energy Load and Power Forecasting(4), Solar Radiation and Photovoltaics(3), Graphite, nuclear technology, radiation studies(3)

Publications20 total

Locating the Source of Oscillation With Two-Tier Dynamic Mode Decomposition Integrating Early-Stage Energy
2025
Deterministic and Probabilistic Forecasting of Wind Power Generation and Ramp Rate With Expectation-Implemented Deep Learning
IEEE Transactions on Sustainable Energy·2025· 2 citedOpen Access
PGLib-CO2: A Power Grid Library for Computing and Optimizing Carbon Emissions
arXiv (Cornell University)·2025Open Access
A study on in-situ characterization technology development for clearance verification of radioactive waste from nuclear decommissioning
Annals of Nuclear Energy·2024
Locating the Source of Oscillation With Two-Tier Dynamic Mode Decomposition Integrating Early-Stage Energy
IEEE Transactions on Power Systems·2023· 7 citedOpen Access
Assessment of indoor air quality and health risk from formaldehyde exposure in postnatal care centers and elderly care facilities in Seoul
Journal of Odor and Indoor Environment·2023· 1 cited
Effect of Safe Pretreatment Process for Contaminated Electric Wire Wastes Generated During Decommissioning in Nuclear Power Plants
SSRN Electronic Journal·2023Open Access
A Study on In-Situ Characterization Technology Development for Clearance Verification of Radioactive Waste from Nuclear Decommissioning
SSRN Electronic Journal·2023· 1 citedOpen Access
A study of the NF3 plasma etching reaction with cobalt oxide films grown on an inorganic compounds
Nuclear Engineering and Technology·2022· 2 citedOpen Access
Deep Concatenated Residual Network With Bidirectional LSTM for One-Hour-Ahead Wind Power Forecasting
2022 IEEE Power & Energy Society General Meeting (PESGM)·2022· 3 cited
Feedforward Error Learning Deep Neural Networks for Multivariate Deterministic Power Forecasting
IEEE Transactions on Industrial Informatics·2022· 13 cited
Estimation of Structural Mechanical Damping in Multi-mass of Turbine Generator for SSTI Study
Journal of Electrical Engineering and Technology·2022· 3 cited
ConvNet-based Remaining Useful Life Prognosis of a Turbofan Engine
2021· 3 cited
Deep Concatenated Residual Network With Bidirectional LSTM for One-Hour-Ahead Wind Power Forecasting
IEEE Transactions on Sustainable Energy·2020· 240 citedOpen Access
Remaining Useful Life Prognosis for Turbofan Engine Using Explainable Deep Neural Networks with Dimensionality Reduction
Sensors·2020· 80 citedOpen Access
Explainable Artificial Intelligence for the Remaining Useful Life Prognosis of the Turbofan Engines
2020· 26 cited
Short-Term Power Load Forecasting of a Large Vessel using Deep Stacking Network Architecture
The Transactions of The Korean Institute of Electrical Engineers·2020· 1 cited
Multivariate Time Series Forecasting for Remaining Useful Life of Turbofan Engine Using Deep-Stacked Neural Network and Correlation Analysis
2020· 22 cited
Multivariate Time Series Forecasting for Remaining Useful Life of Turbofan Engine Using Deep-Stacked Neural Network and Correlation Analysis
IEEE Conference Proceedings·2020
Distribution Voltage Regulation Using Combined Local and Central Control Based on Real-Time Data
2019· 3 cited

Frequent Co-authors

Kyeon Hur(14), Kwangsuk Lee(7), Chang Woo Hong(6), Jae-Kyeong Kim(4), Wooyoung Shin(3), Zhao Yang Dong(2), Changmin Lee(2), Kyungwon Oh(2), Kai Sun(2), Kyung Min Kim(2), Yong Soo Kim(2), Sangtae Kim(2), Kyung-Min Kim(2), Chang Woo Hong(1), DaeEun Kim(1), Hyun-Keun Ku(1), Jiyoung Song(1), Sae-hwan Lim(1), Jae-kyeong Kim(1), Jaeyong Lee(1)