CV
Education
- Ph.D. -Department of Architecture, Graduate School of Engineering, The University of Tokyo, 2021
- M.S. -School of Energy and Environment, Southeast University, 2016
- B.S. -School of Mechanical Engineering, Tongji University, 2013
Work experience
- 2021 to present: Postdoc Researcher
- Institute of Industrial Science, The University of Tokyo
- 2011 to 2012: Intern
- Siemens Real Estate, Siemens Co., Ltd.
Research interests
- AI applications in built environment
- Smart buildings
- Building performance simulation
- CFD in built environment
- Indoor air quality
- Ventilation and airborne infection control
Selected Publications
- Q. Zhou, R. Ooka. Implementation of a coupled simulation framework with neural network and Modelica for fast building energy simulation considering non-uniform indoor environment. Building and Environment, 2022; 211: 108740.
- Q. Zhou, R. Ooka. Performance of neural network for indoor airflow prediction: Sensitivity towards weight initialization. Energy and Buildings, 2021; 246: 111106.
- Q. Zhou, R. Ooka. Influence of data preprocessing on neural network performance for reproducing CFD simulations of non-isothermal indoor airflow distribution. Energy and Buildings, 2020; 230: 110525.
- Q. Zhou, R. Ooka. Comparison of different deep neural network architectures for isothermal indoor airflow prediction. Building Simulation, 2020; 13(6): 1409-1423.
- Q. Zhou, H. Qian, L. Liu. Numerical investigation of airborne infection in naturally ventilated hospital wards with central-corridor type. Indoor and Built Environment, 2018; 27(1): 59-69.
- Q. Zhou, H. Qian, H. Ren, Y. Li, P.V. Nielsen. The lock-up phenomenon of exhaled flow in a stable thermally-stratified indoor environment. Building and Environment, 2017; 116: 246-256.
