Publications of the EIS Lab and its principal investigator. For citation metrics, see Google Scholar.
Working Papers
Adaptive Physics-Guided Network for Cross-Cell State-of-Health Estimation Using Partial-Charging Electrochemical Impedance Spectroscopy.
Ontological Commitments in Knowledge Reuse for Expert Systems: A Preventive Framework.
Quantifying the Value of Operational NWP and Multisite Information for 24-96 h Wind Power Forecasting.
DyG-LA: Dynamic Graph Representation Learning via Linear Attention and Recurrent Matrix States.
TRACE: Transparent Agentic Framework for Natural Language Explanations in Smart Manufacturing.
Submitted / Under Review
RCProb: Probabilistic rule extraction from classification tree ensembles. Submitted to Expert Systems with Applications · 2026-09 · Q1Preprint
Selecting Context for Rule-Grounded Explanation Generation: A Small Language Model Study in Injection Moulding Quality Prediction. Submitted to Processes · 2026-08 · Q3
Journal Articles
2025
FiSC: A Novel Approach for Fitzpatrick Scale-Based Skin Analyzer’s Image Classification. Guillermo Crocker Garcia, Muhammad Numan Khan, Aftab Alam, Josue Obregon, Tamer Abuhmed, Eui-Nam Huh. IEEE Access, vol. 13, pp. 42934–42948.
2024
Rule-based visualization of faulty process conditions in the die-casting manufacturing. Josue Obregon, Jae Yoon Jung. Journal of Intelligent Manufacturing, vol. 35, pp. 521-537. DOI
2024
Multi-step photovoltaic power forecasting using transformer and recurrent neural networks. Jimin Kim, Josue Obregon, Hoonseok Park, Jae Yoon Jung. Renewable and Sustainable Energy Reviews, vol. 200. DOI
2023
RuleCOSI+: Rule extraction for interpreting classification tree ensembles. Josue Obregon, Jae Yoon Jung. Information Fusion, vol. 89, pp. 355-381. DOI
2023
Convolutional autoencoder-based SOH estimation of lithium-ion batteries using electrochemical impedance spectroscopy. Josue Obregon, Yu Ri Han, Chang Won Ho, Devanadane Mouraliraman, Chang Woo Lee, Jae Yoon Jung. Journal of Energy Storage, vol. 60. DOI
2021
Rule-based explanations based on ensemble machine learning for detecting sink mark defects in the injection moulding process. Josue Obregon, Jihoon Hong, Jae-Yoon Jung. Journal of Manufacturing Systems, vol. 60, pp. 392-405. DOI
2019
RuleCOSI: Combination and simplification of production rules from boosted decision trees for imbalanced classification. Josue Obregon, Aekyung Kim, Jae-Yoon Jung. Expert Systems with Applications, vol. 126. DOI
2019
InfoFlow: Mining Information Flow Based on User Community in Social Networking Services. Josue Obregon, Minseok Song, Jae Yoon Jung. IEEE Access, vol. 7, pp. 48024-48036. DOI
2014
Analyzing information flow and context for Facebook fan pages. K. Kim, J. Obregon, J.-Y. Jung. IEICE Transactions on Information and Systems, vol. E97-D. DOI
Book Chapters
2022
Explanation of ensemble models. Josue Obregon, Jae Yoon Jung. Human-Centered Artificial Intelligence: Research and Applications, pp. 51-72. DOI
International Conference Papers
2024
Discovering Dispatching Rules in a Semiconductor Fab Using Interpretable Machine Learning. Minsik Kim, Young-Suk Han, Josue Obregon, Jae-Yoon Jung. International Conference on Flexible Automation and Intelligent Manufacturing, pp. 91-97. DOI
2024
Discovering Dispatching Rules in a Semiconductor Fab Using Interpretable Machine Learning. Minsik Kim, Young-Suk Han, Josue Obregon, Jae-Yoon Jung. International Conference on Flexible Automation and Intelligent Manufacturing, pp. 91–97.
2017
Decision mining in a broader context: An overview of the current landscape and future directions. J. De Smedt, S.K.L.M. Vanden Broucke, J. Obregon, A. Kim, J.-Y. Jung, J. Vanthienen. Business Process Management Workshops, vol. 281. DOI
2014
Constructing decision trees from process logs for performer recommendation. A. Kim, J. Obregon, J.-Y. Jung. Business Process Management Workshops, vol. 171 171 LN. DOI
2013
DTminer: A tool for decision making based on historical process data. J. Obregon, A. Kim, J.-Y. Jung. Asia Pacific Business Process Management, vol. 159. DOI
Domestic Conference Papers
2026
Transparent Agentic Framework for Natural Language Explanation in Smart Manufacturing. Jostin Jerico Rosal, Josue Obregon. 대한산업공학회 추계학술대회 논문집, pp. 341–353.
2026
DyG-LA: Dynamic Graph Representation Learning via Linear Attention and Recurrent Matrix States. Hassanpour Hayatulla, Josue Obregon. 대한산업공학회 추계학술대회 논문집, pp. 125–139.
2026
Adaptive Physics-Gated Network for SOH Estimation from Partial Charging EIS Data of Lithium-Ion Batteries. Raksmey Phann, Josue Obregon. 대한산업공학회 추계학술대회 논문집, pp. 327–335.
2024
Stacking Predictive Models into LLMs: Improving Transparency in Manufacturing Quality Predictions. Josue Obregon. 대한산업공학회 추계학술대회 논문집, pp. 429–436.