International Publications

2024 Publications

Num	Title
76	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
75	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
74	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
73	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
72	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
71	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
70	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.
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

2022 Publications

Num.	Title
45	S. Park, S. Park, S. Yoon, D. Song, Predicting airtightness using differential pressure in actual climate conditions: Theory and implementation, Indoor and Built Environment. (2022). https://doi.org/10.1177/1420326X221131949
44	J. Koo, S. Yoon, In-situ sensor virtualization and calibration in building systems, Applied Energy 325 (2022) 119864. https://doi.org/10.1016/j.apenergy.2022.119864
43	S. Yoon, Virtual sensing in intelligent buildings and digitalization, Automation in Construction. 143 (2022) 104578. https://doi.org/10.1016/j.autcon.2022.104578
42	Y. Hong, S. Yoon, Holistic Operational Signatures for an energy-efficient district heating substation in buildings, Energy. 250 (2022) 123798. https://doi.org/10.1016/j.energy.2022.123798.
41	T. Lee, S. Yoon, K. Won, Delta-T-based operational signatures for operation pattern and fault diagnosis of building energy systems, Energy and Buildings. 257 (2022). https://doi.org/10.1016/j.enbuild.2021.111769.
40	J. Koo, S. Yoon, J. Kim, Virtual In Situ Calibration for Operational Backup Virtual Sensors in Building Energy Systems, Energies (Basel). 15 (2022). https://doi.org/10.3390/en15041394.
39	J. Bak, J. Koo, S. Yoon, H. Lim, Thermal Draft Load Coefficient for Heating Load Differences Caused by Stack-Driven Infiltration by Floor in Multifamily High-Rise Buildings, Energies (Basel). 15 (2022). https://doi.org/10.3390/en15041386.
38	T. Zhao, J. Li, P. Wang, S. Yoon, J. Wang, Improvement of virtual in-situ calibration in air handling unit using data preprocessing based on Gaussian mixture model, Energy and Buildings. 256 (2022). https://doi.org/10.1016/j.enbuild.2021.111735.
37	J. Wang, Z. Huang, Z. Liu, C. Yue, P. Wang, S. Yoon, In-situ sensor correction method for data center cooling systems using Bayesian Inference coupling with autoencoder, Sustainable Cities and Society. 76 (2022). https://doi.org/10.1016/j.scs.2021.103514.
36	S. Yoon, Y. Yu, H. Li, Y. Choi, Y. Hong, Improved energy balance calculation of unitary air conditioners via virtual in-situ calibration, Journal of Building Engineering. 45 (2022). https://doi.org/10.1016/j.jobe.2021.103464.
35	J. Li, P. Wang, T. Zhao, S. Yoon, J. Wang, The effects of multidimensional data clustering on the accuracy of virtual in-situ calibration in the photovoltaic/Thermal heat pump system, Journal of Building Engineering. 45 (2022). https://doi.org/10.1016/j.jobe.2021.103500.

2023 Publications

Num	Title
62	Y. Choi, S. Yoon, In-situ observation virtual sensor in building systems toward virtual sensing-enabled digital twins, Energy and Buildings (2023) 112766. https://doi.org/10.1016/j.enbuild.2022.112766
61	P. Wang, C.Li, M.N. Hossain, S. Yoon, L. Zhao, R. Liang, H. Guan, Research on designated calibration method of fault sensor in PVT heat pump system based on fault detection and virtual calibration, Journal of Building Engineering 76 (2023) 107237, https://doi.org/10.1016/j.jobe.2023.107237
60	R. Liang, C. Wang, P. Wang, S. Yoon, Realization of rule-based automated design for HVAC duct layout, Journal of Building Engineering 80 (2023) 107946, https://doi-org-ssl.sa.skku.edu/10.1016/j.jobe.2023.107946
59	J. Kim, S. Yoon, Virtual PMV sensor towards smart thermostats: Comparison of modeling approaches using intrusive data, Energy and Buildings 301 (2023) 113695, https://doi.org/10.1016/j.enbuild.2023.113695
58	Y. Choi, S. Yoon, Surrogate-assisted high-accuracy observation modeling in building digital twins: In situ modeling without sensor observation (Y), Building and Environment 242 (2023) 110584, https://doi.org/10.1016/j.buildenv.2023.110584
57	S. Yoon, J. Koo, In situ model fusion for building digital twinning, Building and Environment, Building and Environment 243 (2023) 110652, https://doi.org/10.1016/j.buildenv.2023.110652
56	J. Li, P. Wang, X. Han, T. Zhao, S. Yoon, Strategies for sensor virtual in-situ calibration in building energy system: Sensor evaluation and data-driven based method, Energy and Buildings 294 (2023) 113274, https://doi.org/10.1016/j.enbuild.2023.113274
55	S. Yoon, Building Digital Twinning: Data, Information, and Models, Journal of Building Engineering, Journal of Building Engineering (2023) 107021, https://doi.org/10.1016/j.jobe.2023.107021
54	P. Wang, C. Li, R. Liang, S. Yoon, S. Mu, Y. Liu, Fault detection and calibration for building energy system using Bayesian inference and sparse autoencoder: A case study in photovoltaic thermal heat pump system, Energy and Buildings 290 (2023) 113051, https://doi.org/10.1016/j.enbuild.2023.113051
53	S. Yoon, Y. Choi, J. Koo, In situ virtual sensors in building digital twins: framework and methodology, Journal of Industrial Information Integration 36 (2023) 100532, https://doi.org/10.1016/j.jii.2023.100532
52	J. Kim, S. Yoon, J. Koo, J. Bak, J. Lim, In situ virtual sensing for dwelling infiltration rates in multi-unit residential buildings (2023) 106225, https://doi.org/10.1016/j.jobe.2023.106225
51	S. Choi, S. Yoon, Energy signature-based clustering using open data for urban building energy analysis toward carbon neutrality: A case study on electricity change under COVID-19, Sustainable Cities and Society 92 (2023) 104471, https://doi.org/10.1016/j.scs.2023.104471

2021 Publications

Num.	Title
34	J. Bak, S. Yoon, Dwelling infiltration and heating energy demand in multifamily high-rise and low-energy buildings in Korea, Renewable and Sustainable Energy Reviews. 148 (2021). https://doi.org/10.1016/j.rser.2021.111284.
33	Y. Choi, S. Yoon, Autoencoder-driven fault detection and diagnosis in building automation systems: Residual-based and latent space-based approaches, Building and Environment. 203 (2021). https://doi.org/10.1016/j.buildenv.2021.108066.
32	Y. Hong, S. Yoon, Y.S. Kim, H. Jang, System-level virtual sensing method in building energy systems using autoencoder: Under the limited sensors and operational datasets, Applied Energy. 301 (2021). https://doi.org/10.1016/j.apenergy.2021.117458.
31	Z. Liu, Z. Huang, J. Wang, C. Yue, S. Yoon, A novel fault diagnosis and self-calibration method for air-handling units using Bayesian Inference and virtual sensing, Energy and Buildings. 250 (2021). https://doi.org/10.1016/j.enbuild.2021.111293.
30	J. Kim, S. Yoon, J. Koo, J. Bak, Y.S. Kim, TDC-based horizontal leakage area estimation in multiunit residential buildings: Three correction factors, Building and Environment. 192 (2021). https://doi.org/10.1016/j.buildenv.2021.107630.
29	Y. Choi, D. Song, S. Yoon, J. Koo, Comparison of factorial and latin hypercube sampling designs for meta-models of building heating and cooling loads, Energies (Basel). 14 (2021). https://doi.org/10.3390/en14020512.
28	R. Kim, Y. Hong, Y. Choi, S. Yoon, System-level fouling detection of district heating substations using virtual-sensor-assisted building automation system, Energy. 227 (2021). https://doi.org/10.1016/j.energy.2021.120515.
27	P. Wang, K. Han, R. Liang, L. MA, S. Yoon, The virtual in-situ calibration of various physical sensors in air handling units, Science and Technology for the Built Environment. 27 (2021) 691–713. https://doi.org/10.1080/23744731.2020.1798175.

2020 Publications

Num.	Title
26	S. Yoon, D. Song, J. Kim, J. Kim, H. Lim, J. Koo, Identifying stack-driven indoor environmental problems and associated pressure difference in high-rise residential buildings: Airflow noise and draft, Building and Environment. 168 (2020). https://doi.org/10.1016/j.buildenv.2019.106483.
25	H. Lim, J. Seo, D. Song, S. Yoon, J. Kim, Interaction analysis of countermeasures for the stack effect in a high-rise office building, Building and Environment. 168 (2020). https://doi.org/10.1016/j.buildenv.2019.106530.
24	S. Yoon, In-situ sensor calibration in an operational air-handling unit coupling autoencoder and Bayesian inference, Energy and Buildings. 221 (2020). https://doi.org/10.1016/j.enbuild.2020.110026.
23	P. Wang, J. Li, S. Yoon, T. Zhao, Y. Yu, The detection and correction of various faulty sensors in a photovoltaic thermal heat pump system, Applied Thermal Engineering. 175 (2020). https://doi.org/10.1016/j.applthermaleng.2020.115347.
22	Y. Choi, S. Yoon, Virtual sensor-assisted in situ sensor calibration in operational HVAC systems, Building and Environment. 181 (2020). https://doi.org/10.1016/j.buildenv.2020.107079.
21	J. Bak, S. Yoon, D. Song, H. Lim, Y.S. Kim, Weather-driven infiltration and interzonal airflow in a multifamily high-rise building: Dwelling infiltration distribution, Building and Environment. 181 (2020). https://doi.org/10.1016/j.buildenv.2020.107098.
20	P. Wang, J. Li, S. Yoon, T. Zhao, Y. Yu, The detection and correction of various faulty sensors in a photovoltaic thermal heat pump system, Applied Thermal Engineering. 175 (2020). https://doi.org/10.1016/j.applthermaleng.2020.115347.
19	J. Li, T. Zhao, P. Wang, S. Yoon, Y. Yu, Effects of various partitions on the accuracy of virtual in-situ calibration in building energy systems, Journal of Building Engineering. 32 (2020). https://doi.org/10.1016/j.jobe.2020.101538.
18	S. Yoon, Y. Choi, J. Koo, Y. Hong, R. Kim, J. Kim, Virtual sensors for estimating district heating energy consumption under sensor absences in a residential building, Energies (Basel). 13 (2020). https://doi.org/10.3390/en13226013.

~2019 Publications

Num.	Title
17	S. Yoon, Y. Yu, J. Wang, P. Wang, Impacts of HVACR temperature sensor offsets on building energy performance and occupant thermal comfort, Building Simulation. 12 (2019) 259–271. https://doi.org/10.1007/s12273-018-0475-3.
16	P. Wang, S. Yoon, Y. Yu, Z. Shen, Experimental study on the active enhancement mechanisms of heat and mass transfer in an absorption chiller (RP-1462), Science and Technology for the Built Environment. 25 (2019) 58–68. https://doi.org/10.1080/23744731.2018.1498668.
15	J. Wang, Q. Zhang, S. Yoon, Y. Yu, Impact of uncertainties on the supervisory control performance of a hybrid cooling system in data center, Building and Environment. 148 (2019) 361–371. https://doi.org/10.1016/j.buildenv.2018.11.026.
14	J. Wang, Q. Zhang, S. Yoon, Y. Yu, Reliability and availability analysis of a hybrid cooling system with water-side economizer in data center, Building and Environment. 148 (2019) 405–416. https://doi.org/10.1016/j.buildenv.2018.11.021.
13	S. Yoon, D. Song, J. Kim, H. Lim, Stack-driven infiltration and heating load differences by floor in high-rise residential buildings, Building and Environment. 157 (2019) 366–379. https://doi.org/10.1016/j.buildenv.2019.05.006.
12	D. Song, S. Yoon, C. Jeong, J. Kim, H. Lim, Heat, vapor, and CO2 transportation caused by airflow in high-rise residential buildings, Building and Environment. 160 (2019). https://doi.org/10.1016/j.buildenv.2019.106176.
11	P. Wang, S. Yoon, J. Wang, Y. Yu, Automated reviving calibration strategy for virtual in-situ sensor calibration in building energy systems: Sensitivity coefficient optimization, Energy and Buildings. 198 (2019) 291–304. https://doi.org/10.1016/j.enbuild.2019.06.014.
10	J. Wang, Q. Zhang, Y. Yu, X. Chen, S. Yoon, Application of model-based control strategy to hybrid free cooling system with latent heat thermal energy storage for TBSs, Energy and Buildings. 167 (2018) 89–105. https://doi.org/10.1016/j.enbuild.2018.02.036.
9	Y. Wang, P. Wang, S. Yoon, Y. Yu, M. Bai, Characteristics of flow and heat transfer of nanofluids under laminar states, Numerical Heat Transfer; Part A: Applications. 73 (2018) 1–16. https://doi.org/10.1080/10407782.2017.1420298.
8	P. Wang, K. Han, S. Yoon, Y. Yu, M. Liu, The gas-liquid two-phase flow in reciprocating enclosure with piston cooling gallery application, International Journal of Thermal Sciences. 129 (2018) 73–82. https://doi.org/10.1016/j.ijthermalsci.2018.02.028.
7	S. Yoon, Y. Yu, Strategies for virtual in-situ sensor calibration in building energy systems, Energy and Buildings. 172 (2018) 22–34. https://doi.org/10.1016/j.enbuild.2018.04.043.
6	S. Yoon, Y. Yu, Hidden factors and handling strategy for accuracy of virtual in-situ sensor calibration in building energy systems: Sensitivity effect and reviving calibration, Energy and Buildings. 170 (2018) 217–228. https://doi.org/10.1016/j.enbuild.2018.04.017.

2025 Publications

Num	Title
101	G. Lee, S. Choi, Y. Choi, J. Koo, D. Kim, S. Yoon, A two-stage imputation method for enhancing urban building energy data resilience using Bayesian inference, Energy and Buildings 349 (2025) 116515, https://doi.org/10.1016/j.enbuild.2025.116515
100	BIST, Agentic Built Environments: a review, Energy and Buildings 346 (2025) 116159, https://doi.org/10.1016/j.enbuild.2025.116159
99	J. Lee, J. Li, S. Yoon, From design to operation: Multi-agent AI for virtual in-situ modeling of digital twins in BIM, Automation in Construction 179 (2025) 106477, https://doi.org/10.1016/j.autcon.2025.106477
98	J. Li, J. Koo, J. Lee, P. Wang, T. Zhao, S. Yoon, AI agent-driven virtual in-situ calibration for intelligent building digital twins, Energy 339 (2025) 138968, https://doi.org/10.1016/j.energy.2025.138968
97	L. Zhao, S. Kang, S. Yoon, J. Li, P. Wang, Fault diagnosis method for data imbalance in chiller systems based on CWGAN-GP and DS evidence theory fusion, Building and Environment 282 (2025) 113271, https://doi.org/10.1016/j.buildenv.2025.113271
96	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
95	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
94	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
93	J. Li, J. Koo, J. Lee, Y. Li, J. Song, P. Wang, T. Zhao, S. Yoon, AI agent-based virtual model development, diagnosis, and calibration for building digital twins, Journal of Industrial Information Integration 48 (2025) 100990, https://doi.org/10.1016/j.jii.2025.100990
92	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
91	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
90	S. Yoon, J. Song, J. Li, Ontology-enabled AI agent-driven intelligent digital twins for building operations and maintenance, Journal of Building Engineering 108 (2025) 112802, https://doi.org/10.1016/j.jobe.2025.112802

2026 Publications

Num	Title
121	From Design to Operation: An Expert-Governed Agentic Framework for Lifecycle-Computable Engineering Artifacts in the Built Environment, Engineering Applications of Artificial Intelligence (under review)
120	A six-dimensional digital twin framework with LLM- and ontology-driven agentic services for building operations and management, expert systems with applications (submitted)
119	Agentic AI system for autonomous indoor environmental services: from ontology generation to continuous service refinement, Energy (under review)
118	An Agentic AI System for Automated Building Energy Simulation to Quantify Tree-Induced Cooling Energy Savings in Urban Buildings, Building and Environment (under review)
117	Autonomous Process Generator (APG): Decoupling Process Design and Execution for Agentic Building Services, Advanced Engineering Informatic (under review)
116	Any coordinate, any time: city-wide prediction of street-level air temperature across Seoul, Sustainable Cities and Society (under review)
115	Agentic AI system for control loop–level fault detection and diagnosis (CL-FDD) service in building operations, Automation in Construction (under review)
114	Digital twin simulator for closed-loop HVAC control in building operations, Applied Energy (under review)
113	A multi-agent research loop for urban building energy modeling performance improvement using aerial and street view imagery, Energy and Buildings (under review)
112	G. Lee, S. Yoon, A knowledge-based multi-agent system using large language models for automated building energy modeling and simulation service, Energy and Buildings 367 (2026) 117688, https://doi.org/10.1016/j.enbuild.2026.117688
111	A-HOS: An ontology-guided multi-agent framework for automated holistic operational signature analysis in district heating substations, Energy and Buildings (under review)
109	DataNet: linking multi-faceted building energy datasets for effective performance analysis at scale, Energy and Buildings (accepted)
110	A decision-support framework for urban building energy services: AI agent-assisted retrofit prioritization, Cities (under review)
108	Agentic Generation for Urban Building Energy Services: from resources to executable services, Sustainable Cities and Society (under review)
107	J. Yoo, S. Choi, D. Yi, S. Yoon, Urban-scale estimation of window-to-wall ratio from street view imagery via computer vision for improved building energy modeling, Applied Energy 410 (2026) 127549, https://doi.org/10.1016/j.apenergy.2026.127549
106	J. Li, J. Koo, J. Lee, P. Wang, T. Zhao, S. Yoon, Agentic fault detection and diagnosis for building HVAC systems using AI agent, ontology, and diagnosis rules, Building and Environment 289 (2026) 114104, https://doi.org/10.1016/j.buildenv.2025.114104
105	N. Ma, R. Labib, R. Amor, A. Chong, C. Fan, K. Forth, X. Fu, S. Fuchs, T. Hong, N. Klimenkova, J. Koo, S. Li, S. T. McCullough, J. Y. Park, R. Shraga, S. Yoon, L. Zhang, Y. Zhang, Ten questions concerning large language models (LLMs) for building applications, Building and Environment 291 (2026) 114260, https://doi.org/10.1016/j.buildenv.2026.114260
104	J. Koo, S. Yoon, Digital twin synchronization in closed-loop HVAC control for building operations, Automation in Construction 182 (2026) 106723, https://doi.org/10.1016/j.autcon.2025.106723
103	D. H. Yi, S. Choi, D.-W. Kim, S. Yoon, Quantifying Urban building shading effects for data-driven building energy modeling, Building and Environment 289 (2026) 114011, https://doi.org/10.1016/j.buildenv.2025.114011
102	S. M. H. Saif, J. Lee, P. Wang, S. Yoon, Metadata schema for virtual sensors in digital twin-enabled building systems using Brick schema, Journal of Building Engineering 121 (2026) 115650, https://doi.org/10.1016/j.jobe.2026.115650