Federated Concept-Based Models: Interpretable models with distributed supervision
Martin Gjoreski is an Ambizione Fellow supported by the Swiss National Science Foundation (SNSF) and a Scientific Collaborator at the People-Centered Computing Lab, within the Faculty of Informatics at Università della Svizzera italiana (USI). His primary research areas are artificial intelligence — specifically machine learning, federated learning, and explainable AI (XAI) — applied to wearable computing, affective computing, and digital healthcare.
Education & recognition
Martin earned his PhD in Computer Science from the Jožef Stefan Institute in Slovenia under the supervision of Profs. Matjaž Gams and Mitja Luštrek. His doctoral thesis received the Jožef Stefan golden emblem, awarded to outstanding PhD theses in Slovenia. In 2021 he was included in the list of the top 2% scientists in the world for single-year impact.
Professional service
- Associate Editor, ACM IMWUT (Interactive, Mobile, Wearable and Ubiquitous Technologies)
- Board Member, Global SNSF Fellows Network
Marc Langheinrich is a Full Professor for Computer Science at the Università della Svizzera italiana (USI) in Lugano, Switzerland, where he co-leads the People-Centered Computing Lab together with Prof. Silvia Santini. Marc received a masters degree (Diplom) in Computer Science from the University of Bielefeld, Germany, in 1997, and his PhD (Dr. sc.) from the ETH Zürich, Switzerland, in 2005. Starting in the fall of 1995, he spent a year as a Fulbright Scholar at the University of Washington, where he also completed his thesis work in the fields of information retrieval and software agents. In the fall of 1997 he joined NEC Research in Japan, where he worked on projects involving personalization and electronic commerce. From October 1999 to August 2008 he was a researcher at the Institute for Pervasive Computing at ETH Zürich, and he joined USI in September 2008.
Research interests
Marc’s main research interest lies at the intersection of privacy and ubiquitous computing. In a world full of invisible sensory systems, comprehensive digital dossiers could be easily and inconspicuously collected. This poses several challenges to the design of ubiquitous systems: Which communication protocols ensure adequate levels of privacy protection? How can user interfaces be structured to give people control over their personal information? And how feasible is comprehensive protection in a world of countless “smart” devices?
Professional service
- Editor-in-Chief (2018-2023), IEEE Pervasive Computing
- Editor, Dagstuhl Open Access Series in Informatics (OASIcs)
- Director, Master in Management and Informatics, USI Lugano
- Director, Master in Financial Technology and Computing, USI Lugano
- Member, Equal Opportunities Committee, USI Lugano
I am a postdoctoral researcher at the Faculty of Informatics at the Università della Svizzera Italiana (USI) in Lugano, Switzerland, where I work in Prof. Silvia Santini and Prof. Marc Langheinrich’s group. I hold a Ph.D. in Computer Science from the University of Liverpool (UK) and a Master’s degree in experimental particle physics from the University of Pisa (IT), having conducted my thesis work within the Mu2e experiment at Fermi National Laboratory (US).
My research centers on interpretability-by-design: building deep learning models whose reasoning is interpretable by construction rather than explained after training, which makes them steerable and verifiable. To this end, I work on standardizing the underlying theory and code interfaces and on adding structure to the interpretable intermediate space.
Among data modalities, I focus particularly on time series, including forecasting, classification, representation learning, and virtual sensing, which I study through problems in the natural sciences and physiological signals. I am also a co-creator of the open-source machine learning library PyTorch Concepts.