Jin Wen
Jin Wen’s research focuses on advancing sustainable, resilient, and human-centered buildings by integrating artificial intelligence, engineering innovation, and social science. Her work develops AI- and data-driven methods for building control, energy efficiency, and fault detection, enabling buildings to interact with the electric grid, reduce emissions, and improve reliability and performance.
She also studies how indoor environments influence occupant health and behavior, creating models and virtual testbeds that inform building design and operation strategies to promote comfort and well-being. Through interdisciplinary and international collaborations, Wen’s research contributes to smarter, healthier, and more equitable built environments.
In the News
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Recent Publications
Graph-based unsupervised domain adaptation for fault diagnosis of HVAC systems
Ghalamsiah, N., Wen, J., Wu, T., Candan, K. S. & O'Neill, Z., Feb 1 2026, In: Building and Environment. 289, 114055.Research output: Contribution to journal › Article › peer-review
Labeled Datasets for Air Handling Units Operating in Faulted and Fault-free States
Ghalamsiah, N., Wen, J., Li, G., Chen, Y., Lu, X., Fu, Y., Chu, M. & O’Neill, Z., Dec 2026, In: Scientific Data. 13, 1, 15.Research output: Contribution to journal › Article › peer-review
Cleanroom environmental control systems: review of research landscape and control strategies
Guo, M., O’Neill, Z., Yang, Z., Wen, J. & Sun, W., Aug 15 2026, In: Energy and Buildings. 365, 117639.Research output: Contribution to journal › Review article › peer-review
A cyber-resilient control framework with adaptive model predictive control (AMPC) for securing energy systems in smart buildings
Li, G., Fu, Y., O’Neill, Z., Yang, Z., Adetola, V., Wen, J., Ren, L., Wu, T., Zhu, Q., Candan, K. S. & Parikh, C., 2026, In: Science and Technology for the Built Environment. 32, 1, p. 1-24 24 p.Research output: Contribution to journal › Article › peer-review
Scientific machine learning (SciML) for building technology: A new paradigm for design and operations
Liu, M., O'Neill, Z., Wen, J., Wu, T., Dong, B. & Yang, Z., May 15 2026, In: Building and Environment. 296, 114518.Research output: Contribution to journal › Review article › peer-review
Understanding the role of artificial intelligence in improving human well-being within the built environment
Aghaei, A., Pedrielli, G., Wu, T., O’Neill, Z., Becerik-Gerber, B., Hoque, S. & Wen, J., Jul 2025, In: Building Simulation. 18, 7, p. 1727-1742 16 p.Research output: Contribution to journal › Article › peer-review
Advances in supervisory control strategies for a heat pump centric HVAC system − a comprehensive review on applications
Calfa, C. J., O'Neill, Z., Yang, Z., Wen, J., Adetola, V. & Liu, X., Nov 15 2025, In: Applied Thermal Engineering. 279, 128059.Research output: Contribution to journal › Review article › peer-review
Unsupervised domain adaptation for HVAC fault diagnosis using contrastive adaptation network
Ghalamsiah, N., Wen, J., Candan, K. S., Wu, T., O'Neill, Z. & Aghaei, A., Jun 15 2025, In: Energy and Buildings. 337, 115659.Research output: Contribution to journal › Article › peer-review
A framework for calibrating and validating an HVAC system in Modelica
Li, Y., Chen, Z., Wen, J., Fu, Y., Pertzborn, A. & O’Neill, Z., 2025, (Accepted/In press) In: Journal of Building Performance Simulation.Research output: Contribution to journal › Article › peer-review
Large language models for building energy applications: Opportunities and challenges
Liu, M., Zhang, L., Chen, J., Chen, W. A., Yang, Z., Lo, L. J., Wen, J. & O’Neill, Z., Feb 2025, In: Building Simulation. 18, 2, p. 225-234 10 p.Research output: Contribution to journal › Article › peer-review
Developing a weighting scheme for building operational performance: A case study from the Netherlands
Luo, W., Johra, H., Borkowski, E., Liu, X., Wen, J., Ouf, M., Capozzoli, A., Nagy, Z. & Kramer, R., Dec 1 2025, In: Building and Environment. 286, 113762.Research output: Contribution to journal › Article › peer-review
Development of high-fidelity air handling unit fault models for FDD innovation: lessons learned and recommendations
Casillas, A., Chen, Y., Granderson, J., Lin, G., Chen, Z., Wen, J. & Huang, S., 2024, In: Journal of Building Performance Simulation. 17, 5, p. 615-630 16 p.Research output: Contribution to journal › Article › peer-review
Advanced co-simulation framework for assessing the interplay between occupant behaviors and demand flexibility in commercial buildings
Chen, Z., Wen, J., Li, Y., Lo, L. J., Grajewski, G., Payne, W. V., Bushby, S. T., Pertzborn, A., O’Neill, Z., Yang, Z. & Calfa, C., 2024, In: Science and Technology for the Built Environment. 30, 9, p. 1094-1113 20 p.Research output: Contribution to journal › Article › peer-review
An entropy-based causality framework for cross-level faults diagnosis and isolation in building HVAC systems
Huang, J., Ghalamsiah, N., Patharkar, A., Pradhan, O., Chu, M., Wu, T., Wen, J., O'Neill, Z. & Selcuk Candan, K., Aug 15 2024, In: Energy and Buildings. 317, 114378.Research output: Contribution to journal › Article › peer-review
A hardware-in-the-loop (HIL) testbed for cyber-physical energy systems in smart commercial buildings
Li, G., Yang, Z., Fu, Y., O’Neill, Z., Ren, L., Pradhan, O. & Wen, J., 2024, In: Science and Technology for the Built Environment. 30, 5, p. 415-432 18 p.Research output: Contribution to journal › Article › peer-review
