Background

Mathias Ciliberto started his PhD in May 2016 in the Wearable Technologies Lab at the University of Sussex.

He received his M.Sc. degree in Computer Science from the University of Milan, Milan, Italy, in 2015. His master project focused on wearable sensors for sport activity tracking.

His research focuses on wearable technologies for gesture recognition mainly in, but not limited to, sports gestures. His interests include machine learning, and artificial intelligence and activity recognition using wearable computing.

During his research, he did an internship at Unilever R&D where he worked on drinking gesture recognition from poorly annotated data.
He did a second internship at Emteq Ltd, where he was assisting the development of activity recognition systems using smart glasses.

Publications

Mathias Ciliberto, Luis Ponce Cuspinera, and Daniel Roggen. WLCSSLearn: Learning algorithm for template matching-based gesture recognition systems. International Conference on Activity and Behavior Computing, 2019

Sebastien Richoz, Mathias Ciliberto, Lin Wang, Phil Birch, Hristijan Gjoreski, Andres Perez-Uribe, and Daniel Roggen. Human and machine recognition of transportation modes from body-worn camera images. International Conference on Activity and Behavior Computing, 2019

Lin Wang, Hristijan Gjoreski, Mathias Ciliberto, Sami Mekki, Stefan Valentin, and Daniel Roggen. Enabling reproducible research in sensor-based transportation mode recognition with the Sussex-Huawei dataset. IEEE Access 7 (2019) pp. 10870–10891. IEEE, 2019

Mathias Ciliberto, Lin Wang, Daniel Roggen, and Ruediger Zillmer. A case study for human gesture recognition from poorly annotated data. Proceedings of the ACM International Joint Conference and International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018

Lin Wang, Hristijan Gjoreski, Mathias Ciliberto, Sami Mekki, Stefan Valentin, and Daniel Roggen. Benchmarking the SHL recognition challenge with classical and deep-learning pipelines. Proceedings of the ACM International Joint Conference and International Symposium on Pervasive and Ubiquitous Computing and Wearable Computers, 2018

Hristijan Gjoreski, Mathias Ciliberto, Lin Wang, Francisco Javier Ordonez Morales, Sami Mekki, Stefan Valentin, and Daniel Roggen. The University of Sussex-Huawei locomotion and transportation dataset for multimodal analytics with mobile devices. IEEE Access 6 (2018) pp. 42592–42604. IEEE, 2018

Mathias Ciliberto, Luis Ponce Cuspinera, and Daniel Roggen. Complex human gestures encoding from wearable inertial sensors for activity recognition. Proceedings of the International Conference on Embedded Wireless Systems and Networks, 2018

Daniel Roggen, Arash Pouryazdan, and Mathias Ciliberto. BlueSense: designing an extensible platform for wearable motion sensing, sensor research and IoT applications. Proceedings of the International Conference on Embedded Wireless Systems and Networks, 2018.

Mathias Ciliberto, Francisco Javier Ordoñez Morales, Hristijan Gjoreski, Daniel Roggen, Sami Mekki, and Stefan Valentin. High reliability Android application for multidevice multimodal mobile data acquisition and annotation. Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems, 2017

Hristijan Gjoreski, Mathias Ciliberto, Francisco Javier Ordoñez Morales, Daniel Roggen, Sami Mekki, and Stefan Valentin. A versatile annotated dataset for multimodal locomotion analytics with mobile devices. Proceedings of the 15th ACM Conference on Embedded Network Sensor Systems, 2017

Mathias Ciliberto, Daniel Roggen, and Francisco Javier Ordóñez Morales. Exploring human activity annotation using a privacy preserving 3D model. Proceedings of the ACM International Joint Conference on Pervasive and Ubiquitous Computing: Adjunct, 2016