Mobility Information Engineering Lab at ETH Zürich
Welcome to the Mobility Information Engineering Lab (MIE) at ETH Zürich. The MIE Lab is part of the Chair of Geoinformation Engineering at the Institute of Cartography and Geoinformation (IKG).
Our research is centered around analyzing spatio-temporal aspects of human mobility and developing methods to increase its sustainability with information and communication technology (ICT).
For this, we combine competences and methods from diverse fields such as Geographic Information Science (GISc), Artificial Intelligence (AI), Data Mining, Transportation Modeling, Spatial Cognition, and Learning Analytics. Our interests span from location-based services (LBS), trajectory data analysis, agent-based models and simulation, algorithms and models for spatio-temporal information, to mobile learning visualizations and learning analytics.
In our research we also place great value on reproducibility and transparency of our work. For this purpose we publish our code on the MIE Lab Github page, and for example provide the Trackintel Python package to standardise preprocessing steps of mobility data.
Read more about our research in the following core areas:
Location-based services to support people in mobility choices, MaaS offers, sustainability assessments
Spatio-temporal machine learning, analysis, simulation & prediction of human mobility, user profiling and personalization
Vehicle-2-grid strategies, smart charging, impact of drivetrain technologies, spatio-temporal assessments of technology penetration
Our paper “UrbanFusion: Stochastic Multimodal Fusion for Contrastive Learning of Robust Spatial Representations” was accepted to the International Conference on Machine Learning (ICML 2026)! In the paper that was led by Dominik Mühlematter as his master thesis at the MIE lab, we are presenting a new method to learn general embeddings of spatial locations that …
Continue reading “Paper on spatial representation learning accepted to ICML”
We welcome Wolin Jiang who will start his PhD at the MIE Lab on the topic of causal inference for car sharing interventions. Wolin is interested in the interplay between individual travel behavior and mobility stakeholders in urban systems. He is excited about applying causal inference to improve shared mobility. Before joining ETH, he received …
Nina Wiedemann, a postdoctoral researcher at the MIE Lab, has been awarded the Förderpreis Geoinformatik by Runder Tisch GIS e.V. for her dissertation titled “Spatio-temporal effects in GeoAI: from predictability to evaluation.”She presented her work at the Münchner GI Runde on March 19, where she was selected as the award recipient by an independent jury.