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International Publications 

2024 Publications

Num
Title
104
Multi-Agent AI-Driven Virtual In-Situ Modeling for Building Digital Twins Using BIM, Automation in Construction (submitted)
103
AI agent-driven virtual in-situ calibration for intelligent building digital twins, Building and Environment (submitted)
102
Adaptive Sequential Benchmarks for virtual in-situ sensor calibration of Photovoltaic Thermal Heat Pump Sensors, Applied Thermal Engineering (submitted)
101
Fault Diagnosis Method for Data Imbalance in Chiller Systems Based on CWGAN-GP and DS Evidence Theory Fusion, Building and Environment (under review)
100
Urban shading landscapes for advancing data-driven building energy modeling, Landscape and Urban Planning (submitted)
99
Digital twin synchronization in closed-loop feedback-controlled building operations, Advanced Engineering Informatics (under review)
98
L. S. John, S. Yoon, J. Li, P. Wang, Anomaly detection using convolutional autoencoder with residual gated recurrent unit and weak supervision for photovoltaic thermal heat pump system, Journal of Building Engineering 100 (2025) 111694, https://doi.org/10.1016/j.jobe.2024.111694
97
AI agent-based indoor environmental informatics: Concept, methodology, and case study, Building and Environment (accpeted)
96
Identifying occupant behavioral impacts on stack effect in high-rise residential buildings: Field measurements, Building and Environment (accpeted)
95
GPT-based virtual model development, diagnosis, and calibration for building digital twins, Journal of Industrial Information Integration (under review)
94
S. Choi, S. Yoon, AI Agent-Based Intelligent Urban Digital Twin (I-UDT): Concept, Methodology, and Case Studies, Smart Cities 2025, 8(1), 28; https://doi.org/10.3390/smartcities8010028
93
DT-BEMS: Digital twin-enabled building energy management system for building energy efficiency and operational informatics, ENERGY (under review)
92
GPT-based intelligent digital twins for building operations and maintenance, Journal of Building Engineering (under review)
91
Y. Li, J. Lee, J. Li, P. Wang, S. Yoon, Nonintrusive in-situ modeling for unobserved virtual models in digital twin-enabled building HVAC systems: A one-year comparison of physics-based and data-driven approaches in a living laboratory, Journal of Building Engineering 101 (2025) 111811, https://doi.org/10.1016/j.jobe.2025.111811
90
Virtual in-situ calibration for digital twin-synchronized building operations, Energy and Buildings (under review)
89
S. Choi, S. Yoon, GPT-based data-driven urban building energy modeling (GPT-UBEM): Concept, methodology, and case studies, Energy and Buildings 325 (2024) 115042, https://doi.org/10.1016/j.enbuild.2024.115042
88
Autonomous In-situ Modeling for Virtual Building Models in Digital Twins, Expert Systems with Applications (accepted)
87
J. Jing, S. Yoon, J. Joe, E.J. Kim, Y. H. Cho, J. H. Jo, Demonstrating the use of absolute pressure sensors for monitoring stack-driven pressure differences in high-rise buildings, Building and Environment 270 (2025) 112500, https://doi.org/10.1016/j.buildenv.2024.112500
86
J. Song, S. Yoon, Ontology-assisted GPT-based building performance simulation and assessment: Implementation of multizone airflow simulation, Energy and Buildings 325 (2024) 114983. https://doi.org/10.1016/j.enbuild.2024.114983
85
S. Yoon, J. Lee, J. Li, P. Wang, Virtual In-situ Modeling between Digital Twin and BIM for Advanced Building Operations and Maintenance, Automation in Construction 168 (2024) 105823. https://doi.org/10.1016/j.autcon.2024.105823
84
S. Choi, D. Yi, D. Kim, S. Yoon, Multi-source data fusion-driven urban building energy modeling, Sustainable Cities & Society 123 (2025) 106283, https://doi.org/10.1016/j.scs.2025.106283
83
Metadata schema for virtual sensors in digital twin-enabled building systems using Brick schema, Engineering Applications of Artificial Intelligence (submitted)
82
Enhancing 1D Convolutional Neural Network for Fault Detection and Diagnosis of Fan Coil Unit Using Multiple Datasets and Models, Journal of Building Engineering (under review)
81
Research on the sensor fault diagnosis and abnormal data repair of environmental control system in a terminal, Journal of Building Engineering (under review)
80
In-situ sensor calibration and fault-tolerant building HVAC control: an EnergyPlus-Python co-simulation testbed, Building and Environment (under review)
79
A digital twin platform-based sensor fault prediction and reverse traceability approach for smart energy systems, Energy and Buildings (under review)
78
Y. Choi, S. Yoon, Enhancing In-situ model accuracy in building systems with augmentation-based synthetic operation data, Journal of Building Engineering 101 (2025) 111623, https://doi.org/10.1016/j.jobe.2024.111623
77
Sensor fault diagnosis and calibration based on voting mechanism for online application using virtual in-situ calibration and time series prediction, Building and Environment (under review)
76
Model fusion algorithms for digital twinning in built environments, Sustainable Cities and Society (under review)
75
J. Jing, K.H. Ji, S. Yoon, J.H. Jo, A novel method for evaluating stack pressure in real high-rise buildings: optimization of measurement points, Building and Environment 259 (2024) 111661. https://doi.org/10.1016/j.buildenv.2024.111661
74
J. Lee, S. Yoon, Metadata schema for virtual building models in digital twins: VB schema implemented in GPT-based applications, Energy and Buildings 327 (2025) 115039, https://doi.org/10.1016/j.enbuild.2024.115039
73
S. Yoon, Virtual Building Models in Built Environments, Developments in the Built Environment 18 (2024) 100453. https://doi.org/10.1016/j.dibe.2024.100453
72
G. Li, Y. Wu, S. Yoon*, X. Fang, Comprehensive transferability assessment of short-term cross-building-energy prediction using deep adversarial network transfer learning, Energy 299 (2024) 131395, https://doi.org/10.1016/j.energy.2024.131395
71
S. Choi, S. Yoon, Change-point model-based clustering for urban building energy analysis: A case study on electricity energy data in commercial buildings, Renewable and Sustainable Energy Reviews 199 114514, https://doi.org/10.1016/j.rser.2024.114514.
70
Y. Choi, S. Yoon, In-situ backup virtual sensor application in building automation systems toward virtual sensing-enabled digital twins, Case Studies in Thermal Engineering 66 (2025) 105792, https://doi.org/10.1016/j.csite.2025.105792
69
J. Wang, Y. Tian, Z. Qi, L. Zeng, P. Wang, S. Yoon, Sensor fault diagnosis and correction for data center cooling system using hybrid multi-label random Forest and Bayesian Inference, Building and Environment 249 (2024) 111124, https://doi-org-ssl.sa.skku.edu/10.1016/j.buildenv.2023.111124.
68
J. Li, P. Wang, Y. Li, Y. Rezgui, S. Yoon, T. Zhao, Analysis of sensor offset characteristics in building energy systems based on redundant sensors: A case study on variable air volume system, Energy and Buildings 306 (2024) 113957. https://doi.org/10.1016/j.enbuild.2024.113957
67
S. Choi, H. Lim, J. Lim, S. Yoon, Retrofit building energy performance evaluation using an energy signature-based symbolic hierarchical clustering method, Building and Environment 251 (2024) 111206. https://doi.org/10.1016/j.buildenv.2024.111206
66
S. Yoon, J. Lee, Perspective for waste upcycling-driven zero energy buildings, Energy 289 (2024) 130029, https://doi.org/10.1016/j.energy.2023.130029.
65
J. Koo, S. Yoon, Neural network-based nonintrusive calibration for an unobserved model in digital twin-enabled building operations, Automation in Construction 159 (2024). https://doi.org/10.1016/j.autcon.2023.105261
64
P. Wang, J. Sun, S. Yoon, L. Zhao, R. Liang, A global optimization method for data center air conditioning water systems based on predictive optimization control, Energy 295 (2024) 130925, https://doi.org/10.1016/j.energy.2024.130925
63
J. Koo, S. Yoon, Simultaneous in-situ calibration for physical and virtual sensors towards digital twin-enabled building operations, Advanced Engineering Informatics 59 (2024) 102239, https://doi.org/10.1016/j.aei.2023.102239
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성균관대학교 지능형건축설비연구실 (Building Information Science & Technology lab.)

Address: (16419) 경기 수원시 장안구 서부로 2066 성균관대학교 자연과학캠퍼스 제1공학관 21동 21402호

Natural Science Campus: 21402A, 2066, Seobu-ro, Jangan-gu, Suwon, Gyeonggi-do, 16419, Republic of Korea
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