Research on and development of Machine Learning algorithms for statistical analysis and modelling of spatio-temporal (big) data, e.g. - Discovery and recognition of mobility and activity patterns from cellular data using Graphical Models; - Human Activity Recognition (modes of transport and locomotion) in smartphone IMU sensor time series with Neural Networks and Hidden Markov Models. - Unusual event detection and trajectory prediction with motion models learnt from massive historical GPS data. - Predictive modelling of passenger flows in public transport facilities and vehicles.Implementation with Java, Scala/Apache Spark, Python, C/C++.Acquisition and management of national and transnational research projects.Publications: https://scholar.google.com/citations?user=t892xm8AAAAJ

Research cooperation on the topic of "Analyzing mobility patterns with cellular data”.

Research cooperation on the topic of "Monitoring and Control of Bus Performance with Low-Frequency AVL Data”.