6 citations · 17 across the 11 of their papers we have counts for
5 papers · 1 filter
Beyond 9-to-5: A Generative Model for Augmenting Mobility Data of Underrepresented Shift Workers
Haoxuan Ma, Xishun Liao, Yifan Liu +2
This paper addresses a critical gap in urban mobility modeling by focusing on shift workers, a population segment comprising 15-20% of the workforce in industrialized societies yet…
Next-Generation Travel Demand Modeling with a Generative Framework for Household Activity Coordination
Xishun Liao, Haoxuan Ma, Yifan Liu +4
Travel demand models are critical tools for planning, policy, and mobility system design. Traditional activity-based models (ABMs), although grounded in behavioral theories, often…
Learning Universal Human Mobility Patterns with a Foundation Model for Cross-domain Data Fusion
Haoxuan Ma, Xishun Liao, Yifan Liu +4
Human mobility modeling is critical for urban planning and transportation management, yet existing approaches often lack the integration capabilities needed to handle diverse data…
Reconstructing Human Mobility Pattern: A Semi-Supervised Approach for Cross-Dataset Transfer Learning
Xishun Liao, Yifan Liu, Chenchen Kuai +5
Understanding human mobility patterns is crucial for urban planning, transportation management, and public health. This study tackles two primary challenges in the field: the relia…
Deep Activity Model: A Generative Approach for Human Mobility Pattern Synthesis
Xishun Liao, Qinhua Jiang, Brian Yueshuai He +3
Human mobility plays a crucial role in transportation, urban planning, and public health, but current approaches face important limitations. Existing deep learning models tend to o…