Tianze Luo is a Ph.D. student at the Department of Geography and Environmental Sustainability, University of Oklahoma, specializing in the urban geography. He is also a research in (Nature AI Lab). His research focuses on the mechanisms of the urban environment and the interaction of the urban environment with regional and global climate. In particular, he uses state of art technology modeling tools (such as machine learning) to combine observational data, remote sensing technology and climate model output to deepen our understanding of the urban environment. Explore sustainable and resilient urban development, especially nature-based solutions.
He hold a Master’s degree (MLA) in landscape Architecture from the University of Edinburgh and a Bachelor of Agriculture degree in Landscape architecture from Northwest A&F University. His recent work was featured in the ECA graduate show, and his research was included in the journal Energy and Building and international conference on IUFRO.
Tianze’s research interests include urban climate modeling, urban thermal comfort, and natural solutions based on urban trees.
Research Theme
- Impacts of urban climate on human health and decision making
Modeling Urban Climate across Scales. - Natural solutions based on urban geography
The focus is on the mitigation effect of urban trees on the urban thermal environment . - Research on thermal comfort in urban environment
It focuses on the impact of urban thermal environment and pollutant emissions on human health and well-being .
Peer – Review Paper
- SCI: Luo, Tianze., Chen, Mingze*. Advancements in supervised machine learning for outdoor thermal comfort: A comprehensive systematic review of scales, applications, and data types. Energy and Building | https://doi.org/10.1016/j.enbuild.2024.115255.
Conference
- Luo, Tianze., Chen, Mingze*. Smart Canopies: Optimizing Tree Layouts for Enhanced Thermal Comfort — An Edinburgh Case Study | 2024 IUFRO (International Union of Forest Research Organizations)