Lu Li

Assistant Professor
Department of Environmental & Sustainable Engineering
College of Nanotechnology, Science, and Engineering
Li-Lu

Contact

[email protected]
Education
  • PhD, Civil and Environmental Engineering, The Hong Kong University of Science and Technology, 2023
  • Visiting Student Researcher, Department of Architecture, Center for the Built Environment, University of California, Berkeley, 2022
  • MS, Control Science and Engineering, China University of Geosciences, 2019
  • BS, Electrical Engineering and Automation, South China Agricultural University, 2016

About

Dr. Lu Li is an Assistant Professor in the Department of Environmental and Sustainable Engineering at the University at Albany. Before joining UAlbany, she was a tenure-track Assistant Professor at Schreiner University in 2024. Prior to that, she served as a Postdoctoral Researcher in the Department of Mechanical and Aerospace Engineering at Syracuse University.

Research

Lu Li on Google Scholar

Research Interests
  • Indoor Air Quality and Thermal Comfort
  • Applications of Artificial Intelligence and Control in the Built Environment
  • Building Information Modeling, Simulation, Measurement and Design
  • Building Energy and HVAC Systems
  • Digital Twin of Built Environment
  • Smart and Healthy Cities
Publications
  1. Li, L., Mirzabeigi S., Soltanian-Zadeh S., Dong, B., Krietemeyer B., Gao P., Wilson N. & Zhang J. (2025) A High-Performance Multi-Scale Modular-based Green Design Studio Platform for Building and Urban Environmental Quality and Energy Simulations, Sustainable Cities and Society, 106078.
  2. Li, L., He, Y., Ji, Y., Fung, J., & Lau, A. K. (2024) Development of a Mixed Chamber Experimental and CFD Database for Smart Indoor Environmental Control, Building and Environment, 262, 111931.
  3. Li, L., He, Y., Chen, W., Ji Y., Fung, J., & Lau, A. K. (2024) An Integrated Experimental and CFD Analysis of Ceiling-Fan-Integrated Air Conditioning System: Indoor Air Quality and Air Velocity. Building and Environment, 258, 111633.
  4. Lin C., Tang T., Wang Z., Li L., &Guo C. (2024) Incentivizing emission controls toward clean air and carbon neutrality in China: perspectives from a risk-based approach for air quality management, Science of Total Environment.
  5. Li, L., He, Y., Zhang, H., Fung, J., & Lau, A. K. (2023). Enhancing IAQ, thermal comfort, and energy efficiency through an adaptive multi-objective particle swarm optimizer grey wolf optimization algorithm for smart environmental control. Building and Environment, 235, 110235.
  6. Fu, Y., Lin, X., Li, L., Chu, Q., Liu, H., Zheng, X., & Li, C. Y. (2023). A POD-DMD augmented procedure to isolating dominant flow field features in a street canyon. Physics of Fluids, 35(2).
  7. Fu, Y., Lin, X., Li, L., Chu, M., Liu, C., Chen, Z., Li, C. Y. & Tse, K. T.. (2023). The NOx-O3 photochemical reactive air pollutant dispersion around an isolated building—The role of turbulence model and building aspect ratio. Building and Environment, 110906.
  8. Ji, Y., Wang, W., He, Y., Li, L., Zhang, H., & Zhang, T. (2023). Performance in generation: An automatic generalizable generative-design-based performance optimization framework for sustainable building design. Energy and Buildings, 113512.
  9. Li, L., Zhang, Y., Fung, J. C., Qu, H., & Lau, A. K. (2022). A coupled computational fluid dynamics and back-propagation neural network-based particle swarm optimizer algorithm for predicting and optimizing indoor air quality. Building and Environment, 207, 108533.
  10. Li, L., Fu, Y., Fung, J. C., Tse, K. T., & Lau, A. K. (2022). Development of a back-propagation neural network combined with an adaptive multi-objective particle swarm optimizer algorithm for predicting and optimizing indoor CO2 and PM2.5 concentrations. Journal of Building Engineering, 54, 104600.
  11. Li, L., Fu, Y., Fung, J. C., Qu, H., & Lau, A. K. (2021). Development of a back-propagation neural network and adaptive grey wolf optimizer algorithm for thermal comfort and energy consumption prediction and optimization. Energy and Buildings, 253, 111439.
  12. Li, L., & Chen, X. (2019) Optimization of kernel learning algorithm based on parallel architecture. Computing, 102 (8), 1881-1907.
     

Instruction & Advising

Courses

IESE 201 Statics