[1] W. O’Brien, A. Wagner, M. Schweiker, A. Mahdavi, J. Day, M.B. Kjærgaard, S. Carlucci, B. Dong, F. Tahmasebi, D. Yan, T. Hong, B. Gunay, Z. Nagy, C. Miller, C. Berger. Introducing IEA EBC Annex 79: Key challenges and opportunities in the field of occupant-centric building design and operation. Building and Environment, 2020.
[2] T. Hong*, C. Chen, Z. Wang, X. Xu. Linking Human-Building Interactions in Shared Offices with Personality Traits, Building and Environment, 2020.
[3] Z. Wang, J. Wang, Y. He, Y. Liu, T. Hong*. Dimension analysis of subjective thermal comfort metrics based on ASHRAE Global Thermal Comfort Database using Machine learning, Building Engineering, 2020.
[4] C. Chen, T. Hong, et al. Culture, conformity, and carbon? A multi-country analysis of heating and cooling practices in office buildings, Energy Research and Social Science, 2020.
[5] Z. Wang, T. Hong*. Learning occupants' indoor comfort temperature through a Bayesian inference approach for office buildings in United States, Renewable and Sustainable Energy Review, 2019.
[6] W. Wang, T. Hong, N. Xu, X. Xu, J. Chen, X. Shan. Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering, Building and Environment, 2019.
[7] N. Luo, W. Weng, X. Xu, T. Hong, M. Fu, K. Sun. Assessment of occupant-behavior-based indoor air quality and its impacts on human exposure risk: A case study based on the wildfires in Northern California, Science of The Total Environment, 2019. https://doi.org/10.1016/j.scitotenv.2019.05.467
[8] Z. Wang, T. Hong*, M.A. Piette. Predicting plug loads with occupant count data through a deep learning approach, Energy, 2019.
[9] Z. Wang, T. Hong*, M.A. Piette, M. Pritoni. Inferring occupant counts from Wi-Fi data in buildings through machine learning, Building and Environment, 2019.
[10] F.C. Sangogboye, R, Jia, T. Hong, C. Spanos, M.B. Kjærgaard. A Framework for Privacy-Preserving Data Publishing with Enhanced Utility for Cyber-Physical Systems. ACM Transactions on Sensor Networks, 2018.
[11] W. Wang, T. Hong, N. Li, R.Q. Wang, and J. Chen. Linking energy-cyber-physical systems with occupancy predication and interpretation through WiFi probe-based ensemble classification. Applied Energy, 2018.
[12] Z. Wang, T. Hong, R. Jia. Buildings.Occupants: A Modelica package for modeling occupant behavior in buildings. Building Performance Simulation, 2018.
[13] W. Wang, T. Hong, J. Chen. Occupancy prediction through machine learning and data fusion of the environmental sensing and Wi-Fi sensing in buildings, Automation in Construction, 2018.
[14] Z. Belafi, T. Hong, A. Reith. A Critical Review on Questionnaire Surveys in the field of Energy-Related Occupant Behaviour, Energy Efficiency, 2018.
[15] J. An, D. Yan, T. Hong. Clustering and statistical analyses of air-conditioning intensity and use patterns in residential buildings, Energy and Buildings, 2018.
[16] W. Wang, J. Chen, T. Hong, N. Zhu. Occupancy prediction through Markov based feedback recurrent neural network (M-FRNN) algorithm with WiFi probe technology, Building and Environment, 2018.
[17] Z. Deme-Belafi, T. Hong, A. Reith. A Library of Building Occupant Behaviour Models Represented in a Standardised Schema, Energy Efficiency, 2018.
[18] W. Wang, J. Chen, T. Hong. Modeling occupancy distribution in large spaces with multi-feature classification algorithm, Building and Environment, 2018.
[19] S. D’OCa, A.L. Pisello, M. Simone, V.M. Barthelmes, T. Hong, S.P. Corgnati. Human-building interaction at work: Findings from an interdisciplinary cross-country survey in Italy. Building and Environment, 2018.
[20] S. D’OCa, T. Hong, J. Langevin. The Human Dimensions of Energy Use in Buildings: A Review. Renewable and Sustainable Energy Reviews, 2018.
[21] D. Yan, T. Hong, B. Dong, et al. IEA EBC Annex 66: Definition and Simulation of occupant behavior in buildings, Energy and Buildings, 2017.
[22] S. D’OCa, C. Chen, T. Hong, Z. Belafi. Synthesizing building physics with social psychology: An interdisciplinary framework for context and occupant behavior in office buildings. Energy Research and Social Science, 2017.
[23] T. Hong, Y. Chen, Z. Belafi, S. D’Oca. Occupant behavior models: A critical review of implementation and representation approaches in building performance simulation programs. Building Simulation, 2017.
[24] Y. Chen, T. Hong, X. Luo. An agent-based stochastic occupancy simulator. Building Simulation. 2017. (link).
[25] K. Sun, T. Hong. A Framework for Quantifying the Impact of Occupant Behavior on Energy Savings of Energy Conservation Measures. Energy and Buildings, 2017 (link).
[26] Y. Chen, X. Liang, T. Hong, X. Luo. Simulation and visualization of energy-related occupant behavior in office buildings. Building Simulation, 2017 (link).
[27] X. Luo, K.P. Lam, Y. Chen, T. Hong. Performance Evaluation of an Agent-based Occupancy Simulation Model. Building and Environment, 2017 (link).
[28] T. Hong, D. Yan, S. D’Oca, C. Chen. Ten questions concerning occupant behavior in buildings: The big picture. Building and Environment, 2017 (link).
[29] Z. Belafi, T. Hong, A. Reith. Smart building management VS. Intuitive human control — Lessons learnt from an office building in Hungary. Building Simulation, 2017 (link).
[30] K. Sun, T. Hong. A Simulation Approach to Estimate Energy Savings Potential of Occupant Behavior Measures, Energy and Buildings, 2016 (link).
[31] X. Yu, D. Yan, K. Sun, T. Hong, D. Zhu. Comparative Study of the Cooling Energy Performance of Variable Refrigerant Flow Systems and Variable Air Volume Systems in Office Buildings. Applied Energy, 2016 (link).
[32] X. Liang, T. Hong, Q. Shen. Improving the accuracy of energy baseline models for commercial buildings with occupancy data. Applied Energy, 2016 (link).
[33] X. Liang, T. Hong, G. Shen. Occupancy data analytics and prediction: A case study. Building and Environment, 2016 (link).
[34] T. Hong, S.C. Taylor-Lange, S. D’Oca, D. Yan, S. Corgnati. Advances in Research and Applications of Energy-Related Occupant Behavior in Buildings. Energy and Buildings, Engineering Advances, 2015 (link).
[35] D. Yan, W. O’Brien, T. Hong, X. Feng, H. B. Gunay, F. Tahmasebi, A. Mahdavi. Occupant behavior modeling for building performance simulation: current state and future challenges. Energy and Buildings, 2015 (link).
[36] T. Hong, Y. Chen, S.C. Taylor-Lange, H. Sun, D. Yan. An occupant behavior modeling tool for co-simulation. Energy and Buildings, 2015 (link).
[37] T. Hong, S. D’Oca, S.C. Taylor-Lange, W. J.N. Turner, Y. Chen, S. P. Corgnati. An ontology to represent energy-related occupant behavior in buildings. Part II: Implementation of the DNAs Framework using an XML schema. Building and Environment, 2015 (link).
[38] T. Hong, S. D'Oca, W. Turner, S.C. Taylor-Lange. An ontology to represent energy-related occupant behavior in buildings. Part I: Introduction to the DNAs Framework. Building and Environment, 2015 (link)
[39] X. Ren, D. Yan, T. Hong. Data Mining of Space Heating System Performance in Affordable Housing. Building and Environment, 2015 (link).
[40] X. Feng, D. Yan, T. Hong. Simulation of occupancy in buildings. Energy and Buildings, 2015 (link).
[41] S. D’Oca, T. Hong. Occupancy schedules learning process through a data mining framework. Energy and Buildings, 2015 (link).
[42] S. D’Oca, T. Hong. A data-mining approach to discover patterns of window opening and closing behavior in offices. Building and Environment, 2014 (link).
[43] X. Zhou, D. Yan, T. Hong, X. Ren. Data analysis and stochastic modeling of lighting energy use in large office buildings in China. Energy and Buildings, 2014 (link).
[44] C. Li, T. Hong, D. Yan. An insight into actual energy use and its drivers in high-performance buildings, Applied Energy, 2014 (link).
[45] K. Sun, D. Yan, T. Hong, S. Guo. Stochastic Modeling of Overtime Occupancy and Its Application in Building Energy Simulation and Calibration, Building and Environment, 2014 (link).
[46] H.W. Lin, T. Hong. On Variations of Space-heating Energy Use in Office Buildings, Applied Energy, 2013 (link).
[47] W.K. Chang and T. Hong. Statistical Analysis and Modeling of Occupancy Patterns in Open-Plan Offices using Measured Lighting-Switch Data, Journal of Building Simulation, 2013 (link).
[48] W. Turner, T. Hong. A technical framework to describe occupant behavior in buildings, BECC (Behavior Energy and Climate Change), 2013 (link).
[49] H.W. Lin, T. Hong. Occupant Behavior: Impact on Energy Use of Private Offices, ASim, Shanghai, 2012 (link).