团队成员

当前团队成员与毕业成员。

当前成员

博士研究生

  • Changyu Han (UZH)
    2022.02–present
    Modeling Restorative Places from Daily Mobility Data to Explore Functions of Healthy Aging (working title)
  • Lanxi Liu (CAU)
    2025.09–present
    Not decided yet
  • Yangfan Xie (CAU)
    2026.09–present
  • Li Sun (CAU)
    2026.09–present

硕士研究生

  • Yang Wang (CAU)
  • Xinyu Zhang (CAU)
  • Zhengshui Ma (CAU)
  • Baoshuai Yi (CAU)
  • Junpeng Cheng (CAU)
  • Jingxian Shi (CAU)
  • Ye Sun (CAU)
    Modeling the Resilience of Long-period Dynamic Systems: a Case Study of Extreme Precipitation Events on Winter Wheat Harvesting in China (working title)

毕业成员

2026

  • Jingxuan Li (CAU)
    Master's thesis, main advisor
    Robustness of field area calculation algorithms based on agricultural machinery trajectories

2025

  • Mengqi Li (UZH)
    Master's thesis, main advisor
    Quantifying the Impact of Transportation Diversity on Human Mobility Resilience During Extreme Disasters: A Case Study of NYC during Hurricane Ida
  • Joris Senn (UZH)
    Master's thesis, co-advisor (Weibel, Zhou)
    Context-based operator classification for cartographic building generalization: A multimodal deep learning approach
  • Chenxi Jiang (UZH)
    Master's thesis, main advisor
    Indoor-outdoor detection with MOASIS data

2024

  • Guojian Zou (Tongji University)
    2023.11–2024.10
    Visiting PhD student
    Research on Key Algorithms of Deep Learning for Smart Transport Network Operation Status
  • Yelu He (UZH)
    Master's thesis, co-advisor (Weibel, Brucks)
    The influence of traffic-infrastructure characteristics on e-scooter accidents in the city of Zürich
  • Nicola Maiani (UZH)
    Master's thesis, co-advisor (Purves)
    Traffic coverage quality by bike in Switzerland: A comparison of cities' bikeability

2023

  • Jingyi Zhou (Nanjing Normal University)
    2023.2–2023.12
    Visiting PhD student
    Research on generalization method of indoor emergency navigation path considering landmark cognition
  • Linus Rüegg (UZH)
    Master's thesis, co-advisor (Weibel, Phillips)
    LocID – A Unique Object at a Location Identifier: Designing a Global Hierarchical Geographic Identifier that Accounts for Spatial Inaccuracy and Computational Performance
  • Tao Peng (UZH)
    Master's thesis, main advisor
    The Association between Human Mobility and Political, Social, Spatial Factors in the US
  • Adrian Grossenbacher (UZH)
    Master's thesis, main advisor
    Impact of Urban Structure on Mobility During COVID-19: A Polycentricity Perspective
  • Jan Winkler (UZH)
    Master's thesis, main advisor (Weibel, Zhou)
    Exploring Transformer Architecture for Building Generalization in Binary Cartographic Maps
  • Nicolas Beglinger (UZH)
    Master's thesis, main advisor (Weibel, Zhou)
    Vector-based Cartographic Generalization of Roads using Graph Convolutional Neural Networks

2022

  • Jing He (Wuhan University)
    2021.11–2022.10
    Visiting PhD student
    Research on the Poverty Alleviation Effect from the Perspective of Multidimensional Poverty
  • Martin Specker (UZH)
    Master's thesis, main advisor
    Gait Analysis of Older Adults: Filter Comparison and Geographical Context

2021

  • Alexandra-Ioana Georgescu (UZH)
    Master's thesis, main advisor. Now PhD student at UZH
    Optimising Locations for Future Return Car-sharing Services: Case Study of the Swiss Car-sharing Cooperative Mobility
  • Pascal Griffel (UZH)
    Master's thesis, main advisor (Röcke)
    Correlates of Older Adults' Out-of-Home Behaviour: Linking Health and Cognition with Mobility Indicators Derived from GPS-Trajectories
  • Livio Brühwiler (UZH)
    Master's thesis, main advisor
    Predicting Individual Car Accident Risk using G.P.S. Trajectories and Critical Driving Events Data
  • Reetta Vaelimaeki (UZH)
    Master's thesis, main advisor
    The Relationship of Visiting Places and the Health of the Aging: through Spatial Trajectory Data

2018

  • Ursina Boos (UZH)
    Independent research project, main advisor
    Towards Cross-Scale Origin Destination Individual Mobility Networks Using Big Data