7th WideHealth Seminar: Mitja Lustrek

The EU-funded WideHealth project aims to conduct research on pervasive eHealth and establish a sustainable network of research and dissemination across Europe.

Title: Activity recognition with a few twists: Experiences from SHL Challenges 2019 and 2020
Speaker: Mitja Lustrek
When: January 11, 2022 – 16:00 CET
Where: zoom link shared before the session to those who register
Registration link:

Abstract: Sussex-Huawei Locomotion (SHL) Dataset was recorded by three people carrying four phones in different locations on their bodies for seven months. It is labelled with eight locomotion activities: still, walking, running, biking, car, bus, train and subway. It was used in three machine-learning competitions organized in collaboration with the HASCA workshop at the Ubicomp conference in 2018–20. While the 2018 challenge presented a relatively standard activity-recognition problem, 2019 and 2020 introduced a few twists. In 2019, the goal was to recognize activities with the phone in the hand location, while most of the training data was provided for the other three locations. In 2020, the goal was to recognize activities with the phone in an unknown location when carried by two different persons, while most of the training data was provided for the third person. The talk will explain how the team from Jozef Stefan Institute tackled these twists with cross-location transfer learning, machine learning to identify the unknown phone location, and trying to separate the persons with clustering.

Short bio: Mitja Lustrek received his PhD degree from the Faculty of Computer and Information Science of the University of Ljubljana in 2007. He was a postdoc at the Institute for Biostatistics and Informatics in Medicine and Ageing Research in Rostock, Germany in 2010. He has worked at the Department of Intelligent Systems at Jozef Stefan Institute, Ljubljana, Slovenia ever since. He is currently employed there as a senior research associate and the head of the Ambient Intelligence Group. His main research interest is the analysis of sensor and other data related to human health and behavior using machine learning. He has been the principal investigator in a number of international research projects on this topic. He was a member of the teams scoring highly in several computer-science competition, such as the XPrize Pandemic Response Challenge and Tricorder competition, EvAAL competition and Sussex-Huawei Locomotion Challenge 2018-2020. He also served as the chair of the Slovenian Artificial Intelligence Society.