Graph Based Machine Learning Methods for Human Mobility Analysis
Henry Martin is a PhD Student in Geoinformatics at the Chair of Geoinformation Engineering at ETH Zurich and at the Institute of Advanced Research in Artificial Intelligence (IARAI). Since 2017 he works at the Mobility Information Engineering (MIE) Lab, where he analyzed the mobility behavior of early Swiss mobility as a service (MaaS) adopters within the SBB Green Class pilot studies and was part of the team that won the second place at the NeurIPS 2019 Traffic4cast competition. In his PhD he is interested in applying modern data analysis methods to spatio-temporal problems related to human mobility and investigating the role of mobility in our way towards a more sustainable energy system.
Event Date: 13 July 2020, 5pm CET.
How can we use graph neural networks for the decarbonization of the transport sector? And why would we?!
These are the main questions that will be leading through the talk that starts with an overview of the recent research done by the MIE Lab at ETH Zurich. The main part of the talk will then be dedicated on how graph-based machine learning methods such as graph neural networks can be applied to problems that are important for the decarbonization of the mobility sector.
