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Xu Han PhD

Assistant Professor

A man with short black hair and dark-rimmed glasses smiles slightly while wearing a black suit jacket and white shirt.
Phone
+1 574-631-8084
Office
325 Walsh Family Hall
Notre Dame, IN 46556

Dr. Xu Han is an Assistant Professor at the School of Architecture and a concurrent Assistant Professor at the College of Engineering, University of Notre Dame, USA. His primary research areas include sustainable buildings and cities, smart buildings and controls, machine learning for built environment applications. His current efforts focus on climate-responsive building design, scalable digital-twin methods, occupant-centric HVAC control, IoT enabled smart buildings, and sustainable and resilient cities to support high-performance, low-carbon built environments.

Based on his research, Dr. Han received the IBPSA Innovative Application Award 2025, the 2024 Best Paper Award from ASHRAE, the Best Poster Award at the IBPSA-USA SimBuild 2024 conference at Denver, CO, the Best Paper Award from the 5th International Conference on Building Energy and Environment (COBEE 2022) at Montreal, Canada, and the 2015 Best Paper Awards from the journal Building and Environment. He serves as the Early Career Board Member of the journal Energy and Buildings and the Journal of Building Performance Simulation, the co-chair of the 3rd ACM International Workshop on Big Data and Machine Learning for Smart Buildings and Cities (ACM BALANCE 2023), scientific committee member for multiple international conferences.

Prior to joining the University of Notre Dame, Dr. Han was an Assistant Professor in Architectural Engineering at the University of Kansas. Dr. Han received his Ph.D. in Architectural Engineering at the University of Colorado Boulder, with a focus on computational tool development for energy efficient data centers. After graduation, Dr. Han became a Postdoctoral Fellow and Research Associate at the Harvard Center for Green Buildings and Cities at Harvard University, where his research emphasized on zero-energy buildings, passive technologies and environment-responsive building design. 

Education

Postdoc, Harvard Center for Green Buildings and Cities, Harvard University, 2020-2023
Ph.D., Architectural Engineering, University of Colorado Boulder, 2020
M.E., Architectural Engineering, Tianjin University, China, 2014
B.E., Architectural Engineering, Harbin Institute of Technology, 2011

Select Publications

  • Han, X.*, Malkawi, A., Li, Z., Zhang, R. and Li, N., 2025. Optimizing Radiant Floor Heating Control with Night Setbacks Using Model-Free Reinforcement Learning and Transfer Learning. Building and Environment, p.113771. (*corresponding author) https://doi.org/10.1016/j.buildenv.2025.113771
  • Li, Z., Tian, J., Ji, G., Cheng, T., Loftness, V. and Han, X.*, 2025. Reinforcement Learning-Enabled Adaptive Control for Climate-Responsive Kinetic Building Facades. Buildings (2075-5309), 15(16). https://doi.org/10.3390/buildings15162977
  • A. Malkawi, S. Ervin, X. Han*, E.X. Chen, S. Lim, et., al, 2023. “Design and Applications of an IoT Architecture for Data-Driven Smart Building Operations and Experimentation”. Energy and Buildings, p. 113291. https://doi.org/10.1016/j.enbuild.2023.113291
  • J.M. Han, S. Lim, A. Malkawi, X. Han*, E.X. Chen, S. Salimi, T.H. Dokka, T. Hegli, K. Edwards, 2023. “Data-Informed Building Energy Management (DiBEM) towards Ultra-Low Energy Buildings”. Energy and Buildings, 281, p.112761. https://doi.org/10.1016/j.enbuild.2022.112761
  • B. Yan1, X. Han1*, A. Malkawi, T.H. Dokka, P. Howard, J. Knowles, T. Hegli, and K. Edwards, 2022. “Comprehensive assessment of operational performance of coupled natural ventilation and thermally active building system via an extensive sensor network”. Energy and Buildings, 260, p.111921. (1contribute equally). https://doi.org/10.1016/j.enbuild.2022.111921
  • X. Han, W. Tian, J. VanGilder, W. Zuo, C. Faulkner 2021. “An Open Source Fast Fluid Dynamics Model for Data Center Thermal Management”. Energy and Buildings. 230, pp. 110599. https://doi.org/10.1016/j.enbuild.2020.110599
  • X. Han, J. Pei, J. Liu, L. Xu 2013. “Multi-objective building energy consumption prediction and optimization for eco-community planning”. Energy and Buildings, 66(5), 22-32. https://doi.org/10.1016/j.enbuild.2013.07.016 

Courses

ARCH 40411 + 70411 – Environmental Systems I
ARCH 50419 + 70419 – Environmental Systems II

Areas of Expertise

  • Architectural Technology/Building Technology
  • Built Environment and Health
  • Research methodology
  • Sustainable Architecture and Urbanism