πŸ“’ We're hiring! MoS Lab 2027 ηΊ§εšε£«ζ‹›η”ŸθΏ›θ‘ŒδΈ­ β€”β€” ζŸ₯ηœ‹ζ‹›η”ŸδΏ‘ζ― β†’

MoS Lab

Mobility Science Lab at Tsinghua University

MoS Lab develops models, algorithms, and data-driven tools for public transit operations, passenger behavior, mobility demand, urban resilience, and sustainable transportation policy.

Explore Research View Publications Join Us
45 publications and working papers
31 journal articles
4 research directions

Featured Research

From passenger-level behavior to city-scale resilience.

Schematic of the individual path recommendation problem on a disrupted rail and bus network (Figure 1, Transportation Science)
Public Transit Resilience

Individual path recommendation under transit disruptions

Models passenger behavior uncertainty and recommends resilient paths during service disruptions.

Read paper
Commuting patterns in Beijing, Munich, and Singapore before and after housing exchange (Figure 2, Nature Sustainability)
Sustainable Urban Systems

Housing exchange to reduce commuting emissions

Uses household-level housing exchange strategies to reduce excess commuting emissions.

Read paper
Pair-wise attention-based pointer neural network architecture (Figure 2, Transportation Research Part E)
Mobility AI

Last-mile delivery route prediction

A pair-wise attention-based pointer neural network that predicts drivers' route trajectories in last-mile delivery.

Read paper
Physical network and time-space hypernetwork representation (Figure 1, Transportation Science)
Public Transit Resilience

Ex post path choice estimation

Estimates urban rail passenger path choices from smart card data via an aggregated time-space hypernetwork.

Read paper

Research Areas

Mobility science for systems that can adapt.

Public transit resilience Disruption management, passenger response inference, path recommendation, and resilient operations.

Travel behavior and demand Route choice, mode choice, smart card analytics, and policy response modeling.

AI for mobility and logistics Robust learning, interpretable prediction, ETA, last-mile delivery, and time-series models.

Sustainable urban systems Commuting emissions, public health risk, housing mobility, and cyber-physical-social resilience.

Research Support

National Natural Science Foundation of China ByteDance

Collaborating Institutions

Massachusetts Institute of Technology Northeastern University UC Berkeley The University of Hong Kong Peking University Tongji University KTH Royal Institute of Technology Zhejiang University National University of Singapore Capital Normal University

News

2026/03/16

New paper: Resilience analysis of urban cyber-physical-social systems appeared in Reliability Engineering and System Safety.

2025/11/01

New paper: Housing exchange framework to reduce carbon emissions from commuting appeared in Nature Sustainability.

2025/10/24

New paper: Individual Path Recommendation Under Public Transit Service Disruptions Considering Behavior Uncertainty appeared in Transportation Science.

2025/05/30

New paper: Robust binary and multinomial logit models for classification with data uncertainties appeared in European Journal of Operational Research.

... see all News