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InclusiViz: Visual Analytics of Human Mobility Data for Understanding and Mitigating Urban Segregation
The Hong Kong University of Science and Technology
Department of Computer Science and Engineering
MPhil Thesis Defence
Title: "InclusiViz: Visual Analytics of Human Mobility Data for
Understanding and Mitigating Urban Segregation"
By
Mr. Yue YU
Abstract:
Urban segregation refers to the physical and social division of people,
often driving inequalities within cities and exacerbating socioeconomic and
racial tensions. While most studies focus on residential spaces, they often
neglect segregation across "activity spaces" where people work, socialize,
and engage in leisure. Human mobility data offers new opportunities to
analyze broader segregation patterns, encompassing both residential and
activity spaces, but challenges existing methods in capturing the complexity
and local nuances of urban segregation. This work introduces InclusiViz, a
novel visual analytics system for multi-level analysis of urban segregation,
facilitating the development of targeted, data-driven interventions.
Specifically, we developed a deep learning model to predict mobility
patterns across social groups using environmental features, augmented with
explainable AI to reveal how these features influence segregation. The
system integrates innovative visualizations that allow users to explore
segregation patterns from broad overviews to fine-grained detail and
evaluate urban planning interventions with real-time feedback. We conducted
a quantitative evaluation to validate the model's accuracy and efficiency.
Two case studies and expert interviews with social scientists and urban
analysts demonstrated the system's effectiveness, highlighting its potential
to guide urban planning toward more inclusive cities.
Date: Wednesday, 16 July 2025
Time: 2:00pm - 4:00pm
Venue: Room 3494
Lifts 25/26
Chairman: Dr. Arpit NARECHANIA
Committee Members: Prof. Huamin QU (Supervisor)
Prof. Cameron CAMPBELL (Co-supervisor, SOSC)
Dr. Qifeng CHEN