Bertil Chapuis

Teaching and research assistant – PhD Candidate – Distributed Object Programming Lab (DopLab)
Université de Lausanne
Département des Systéms d’Information (ISI)
Faculté des Hautes Etudes Commerciales (HEC)



Quartier UNIL-Dorigny ,  Bâtiment Internef
Office: 128.3,  CH-1015 Lausanne
Phone: 021 692 35 80
Email: firstname.lastname at unil dot ch


Bertil Chapuis is a research and teaching assistant at the University of Lausanne, Switzerland. He joined the Distributed Object Programming Lab in 2013. Bertil’s research focuses on next-generation geographic information systems and spans mobility prediction, spatial data storage, indexation and location-aware publish/subscribe. Prior and in parallel to Unil, Bertil shows a strong interest for entrepreneurship. He ran a small software engineering company for four years and co-founded a startup called Astrocast.


Bertil Chapuis and Benoît Garbinato.
Geodabs: Trajectory indexing meets fingerprinting at scale.
In Distributed Computing Systems (ICDCS), 2018 IEEE 38th International Conference on. IEEE, 2018

Vaibhav Kulkarni, Arielle Moro, Bertil Chapuis, and Benoît Garbinato.
Capstone: Mobility modeling on smartphones to achieve privacy by design.
arXiv preprint arXiv:1802.07132, 2018

Bertil Chapuis, Benoît Garbinato, and Periklis Andritsos.
An efficient type-agnostic approach for finding sub-sequences in data.
In High Performance Computing and Communications; IEEE 15th International Conference on Smart City; IEEE 3rd International Conference on Data Science and Systems (HPCC/SmartCity/DSS), 2017 IEEE 19th International Conference on, pages 270–277. IEEE, 2017

Bertil Chapuis, Benoît Garbinato, and Lucas Mourot.
A horizontally scalable and reliable architecture for location-based publish-subscribe.
In Reliable Distributed Systems (SRDS), 2017 IEEE 36th Symposium on, pages 74–83. IEEE, 2017

Bertil Chapuis and Benoît Garbinato.
Scaling and load testing location-based publish and subscribe.
In Distributed Computing Systems (ICDCS), 2017 IEEE 37th International Conference on, pages 2543–2546. IEEE, 2017

Vaibhav Kulkarni, Arielle Moro, Bertil Chapuis, and Benoît Garbinato.
Extracting hotspots without a-priori by enabling signal processing over geospatial data.
In Proceedings of the 25th ACM SIGSPATIAL Intern tional Conference on Advances in Geographic Information Systems, page 79. ACM, 2017

Vaibhav Kulkarni, Bertil Chapuis, and Benoît Garbinato.
Privacy-preserving location-based services by using intel sgx.
In Proceedings of the First International Workshop on Human-centered Sensing, Networking, and Systems, pages 13–18. ACM, 2017

Bertil Chapuis, Arielle Moro, Vaibhav Kulkarni, and Benoît Garbinato.
Capturing complex behaviour for predicting distant future trajectories.
In Proceedings of the 5th ACM SIGSPATIAL International Workshop on Mobile Geographic Information Systems, pages 64–73. ACM, 2016

Bertil Chapuis, Benoît Garbinato, and Periklis Andritsos.
Throughput: A key performance measure of content-defined chunking algorithms.
In Distributed Computing Systems Workshops (ICDCSW), 2016 IEEE 36th International Conference on, pages 7–12. IEEE, 2016

Bertil Chapuis and Benoît Garbinato.
Knowledgeable chunking.
In International Conference on Networked Systems, pages 456–460. Springer, Cham, 2015