About me

I am a PhD candidate at the Urban Analytics Lab, National University of Singapore. My research interests lie at the intersection of urban morphology, spatial perception, and deep learning, with a special focus on Street View Imagery (SVI), its usability and uncertainty as a research tool. I am currently engaged in investigating and simulating the complexity of human visual perception in 3D built environments.

Education

• Doctor of Philosophy, Architecture, National University of Singapore (on going)
• Master of Research, Spatial Data Science and Visualisation, University College London
• Master of Science, Space Syntax: Architecture and Cities, University College London

Research Interest

SVI and its 3D Potential

My research involves developing computational methods for 3D urban environment analysis. The following visualizations demonstrate SVI based reconstruction techniques used in urban perception studies:

Day scene point cloud reconstruction

Night scene point cloud reconstruction

The method has been added to ZenSVI a powerful toolset for collecting and analyzing SVI for scalable urban research. I am also involved in the development of Voxcity, is a Python package that provides a seamless solution for grid-based 3D city model generation and urban simulation for cities worldwide.

Multie-modality Perception of Urban Environment

I have led and developped the Nighttime SVI project, to broadly collect day-night paired SVI across Singapore, and apply the data to map street-level lighting conditions across the city. The project was reported in Nanyang Sin-Chew Lianhe Zaobao, the largest Chinese newspaper in Singapore and featured in the front page.

Example of nighttime Street View Imagery collected in Singapore