Mengxue Yao – Academic Profile

Mengxue Yao MUNG-shweh YOW

PhD, AFHEA

University of Sheffield | myao11@sheffield.ac.uk

About Me

Mengxue Yao is a PhD candidate specializing in air pollution prediction, urban form characteristic quantification, vegetation and urban air quality modelling. Her research involves handling, processing, analyzing, and visualizing large datasets by integrating multiple data sources. The goal of her work is to contribute to improved air quality and the creation of livable urban environments through data-driven urban planning and design.

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Interests

Urban Air Quality and Pollution Modeling
Population Exposure and Public Health
Nature-based Solutions and Green Infrastructure
Data-driven Quantification and Spatial Analysis
Numerical Simulation - CFD and Mechanistic Modeling
AI-based Algorithms - Machine Learning & Deep Learning

Education

PhD in Architecture
University of Sheffield (TUOS)
MEng in Landscape Architecture
Harbin Institute of Technology (HIT)
BEng in Landscape Architecture
Northeast Agricultural University (NEAU)

📚 My Research

My work sits at the intersection of environmental modeling, urban form analysis, and data science.

I develop tools and frameworks to quantify how urban form, vegetation, and human activity interact to shape PM2.5 distribution across time and space. This involves integrating machine learning and deep learning techniques (e.g., street view image segmentation, random forest), spatial clustering, and AI-based predictive modeling using remote sensing and monitoring data.

I am also interested in high-resolution, city-scale data collection and analysis, and in exploring how AI-driven, big-data tools could support data-informed urban policy and design for healthier, more breathable environments.

Please feel free to reach out to collaborate 😃

Featured Publications