Welcome!
I am Ye Hong, a postdoctoral researcher at ETH Zurich, affiliated with the Mobility Information Engineering (MIE) Lab at the Chair of Geoinformation Engineering. I also hold a joint appointment at the University of Zurich’s Department of Geography, where I work with the Urban Analytics Group.
I received my Doctor of Science degree from ETH Zurich, under the supervision of Prof. Martin Raubal and Prof. Konrad Schindler. Before that, I obtained a master’s degree in Geomatics from ETH Zurich and a bachelor’s degree in Geographic Information Science and Remote Sensing from Sun Yat-sen University, China.
My research interests lie at the intersection of human mobility, urban computing, and network science. My work centers on applying machine learning and deep learning techniques to understand, predict, and model individual mobility behavior. The overarching aim of my work is to develop computational frameworks that enable personalized travel solutions and facilitate the transition toward sustainable and intelligent transportation systems.
News
- [05.2025] I gave a talk at the STRC ‘25 titled Causal Inference for interpretable and robust deep learning in mobility analysis.
- [05.2025] Our paper A causal intervention framework for synthesizing mobility data and evaluating predictive neural networks was published in TRIP.
- [05.2024] I gave a talk at the STRC ‘24 titled Towards realistic individual activity location demand synthesis using deep generative networks.
- [04.2024] Our paper Is a 15-Minute City Within Reach? Measuring Multimodal Accessibility and Carbon Footprint in 12 Major American Cities was published in Land Use Policy.
- [11.2023] Our study on travel mode detection - Evaluating geospatial context information for travel mode detection was published in JTRG.
- [08.2023] Our study Context-aware multi-head self-attentional neural network model for next location prediction was published in TRC.
- [07.2023] Our paper Influence of tracking duration on the privacy of individual mobility graphs was published in Journal of Location Based Services.
- [07.2023] Our paper Predicting mobile users’ next location using the semantically enriched geo-embedding model and the multilayer attention mechanism was published in CEUS.
- [07.2023] We have a new paper Predicting visit frequencies to new places accepted at GIScience ‘23.
- [07.2023] Our paper Trackintel: An open-source Python library for human mobility analysis was published in CEUS.
- [12.2022] Our study Conserved quantities in human mobility: from locations to trips was published in TRC.
Publications
Is a 15-Minute City Within Reach? Measuring Multimodal Accessibility and Carbon Footprint in 12 Major American Cities
Land Use Policy, 2025
Predicting mobile users' next location using the semantically enriched geo-embedding model and the multilayer attention mechanism
Computers, Environment and Urban Systems, 2023
Conserved quantities in human mobility: From locations to trips
Transportation Research Part C: Emerging Technologies, 2023
Hierarchical community detection and functional area identification with OSM roads and complex graph theory
International Journal of Geographical Information Science, 2019