Research Fellow / Assistant – ML and Urban Planning

Job Position

Singapore University of Technology and Design’s Meta Design Lab (MDL) working closely with the Lee Kuan Yew Centre for Innovative Cities (LKYCIC) is calling for a Postdoctoral Fellow for an exciting new project, which will be collaborating with Singapore’s National Parks Board (NParks).

Project Description

This project aims to investigate the relationship between macro-urban configurations and its effect on the wellness of residents, focusing specifically in recreation spaces like parks. It hypothesises that much of a resident’s exercise and positive health aspects of a city are a product of how people use an interact with urban spaces. However, the relationship between spatial configuration and activity has not been empirically correlated specially not by observation and data at scale. This research aims to take a significantly more analytical and spatially focused approach, considering and ideally correlating how an urban area effects users’ activity and decisions. Expanding the domain of urban population health research, and related methodological approaches.

To do this it will explore and integrate three concurrent areas of study:

The position advertised here focuses on supporting the first section of this and is intended to be develop a data driven approach to urban recreation analysis, by providing insight into how people use space by using ethical and anonymised image tracking of users of public spaces developing or and/or using ML models to improve aggregate user monitoring and identification of activity and location. This will be correlated with spatial configuration of the spaces, origin-destination modelling, and available route choice analysis (spatial network) provided though other tracking methods. Then using this empirical data as the input source to do analytics for human insight and potentially exploring machine learning to predict space use, computing resultant health metrics, leading to automated appraisal of the wellness of the space.

It is hoped that this work if proven successful may be scaled to wider analysis of recreation areas where possible to develop data for use in deriving more insight into user activity in tandem with the ethnographic study as data triangulation. Combing both these sources to allow for better informed developing of policy and design guidelines to improve future park and recreation space design, potentially building more user focused ML tools for urban planners specifically NParks and other agencies.

The research is highly disciplinary but anchored in Big-Data, Design, Urban Planning, and Applied A.I. and lead by, Belinda Yuen (LKYCIC), Sam Joyce (SUTD), Yuen Chau (SUTD), and Falk Müller-Riemenschneider (NUS) each covering aspects of planning for wellness, applied computational design, A.I., and clinical analysis of recreation spaces respectively.