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International Publications 

2025 Publications

Num
Title
104
Multi-Agent AI-Driven Virtual In-Situ Modeling for Building Digital Twins Using BIM, Automation in Construction (under review)
103
AI agent-driven virtual in-situ calibration for intelligent building digital twins, Building and Environment (under review)
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
J. Hwang, S. Yoon, AI agent-based indoor environmental informatics: Concept, methodology, and case study, Building and Environment 277 (2025) 112879, https://doi.org/10.1016/j.buildenv.2025.112879
96
J. Song, J. Kim, J. Jo, K. Kang, S. Yoon, Identifying occupant behavioral impacts on stack effect in high-rise residential buildings: Field measurements, Building and Environment 277 (2025) 112866, https://doi.org/10.1016/j.buildenv.2025.112866
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
J. Hwang, J. Kim, S. Yoon, DT-BEMS: Digital twin-enabled building energy management system for building energy efficiency and operational informatics, ENERGY (2025) 136162, https://doi.org/10.1016/j.energy.2025.136162
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 (accepted)
89
J. Lee, J. Li, S. Yoon, Autonomous In-situ Modeling for Virtual Building Models in Digital Twins, Expert Systems with Applications 278 (2025) 127289, https://doi.org/10.1016/j.eswa.2025.127289
88
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
87
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
86
Metadata schema for virtual sensors in digital twin-enabled building systems using Brick schema, Engineering Applications of Artificial Intelligence (submitted)
85
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)
84
Research on the sensor fault diagnosis and abnormal data repair of environmental control system in a terminal, Journal of Building Engineering (under review)
83
In-situ sensor calibration and fault-tolerant building HVAC control: an EnergyPlus-Python co-simulation testbed, Building and Environment (under review)
82
A digital twin platform-based sensor fault prediction and reverse traceability approach for smart energy systems, Energy and Buildings (under review)
81
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
80
Sensor fault diagnosis and calibration based on voting mechanism for online application using virtual in-situ calibration and time series prediction, Building and Environment (accepted)
79
J. Lee, P. Wang, S. Yoon, Model fusion algorithms for digital twinning in built environments, Sustainable Cities and Society 125 (2025) 106343, https://doi.org/10.1016/j.scs.2025.106343
78
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
77
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
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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
Tel: 031) 290-7581

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