Martin Gjoreski

I am an Ambizione Fellow funded by the Swiss National Science Foundation (SNSF) and a Scientific Collaborator at the Faculty of Informatics, Università della Svizzera italiana (USI), Switzerland. My research focuses on Responsible AI, with particular emphasis on machine learning, federated and privacy-preserving learning, and explainable AI. I develop and apply these methods in the context of wearable computing, affective computing, and digital health, with the aim of building robust and human-centred AI systems for real-world deployment. I have also held visiting researcher positions and research stays at the University of Cambridge, the MIT Media Lab, the University of Queensland, and Fraunhofer IIS. Alongside my research activities, I serve as a lecturer at USI. In the Autumn semester (2024/25), I taught Mobile and Wearable Computing to MSc and PhD students, followed by Computer Networking for BSc students in the Spring semesters of 2025 and 2026.

Prior to this, I was a postdoctoral researcher at the People-Centered Computing Lab, a research group headed by Professors Marc Langheinrich and Silvia Santini at USI. I earned my PhD in Computer Science from the Jozef Stefan Institute in Slovenia under the supervision of Professors Matjaz Gams and Mitja Lustrek. My thesis was recognized with the prestigious “Jožef Stefan golden emblem,” indicating an outstanding PhD thesis in Slovenia. In 2021, I was honored to be included in the “list of the top 2% scientists in the world,” in the category “single year impact – 2021”. As of 2023, I serve as an Associate Editor at IMWUT (ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies); and as a Board Member at the Global SNSF Fellows Network.

I am actively involved in supervising PhD, MSc, and BSc students, and regularly offer new research projects. Interested students are welcome to contact me by email.

My research focuses on Responsible AI, with particular emphasis on machine learning, federated and privacy-preserving learning, and explainable AI. I develop and apply these methods in the context of wearable computing, affective computing, and digital health, with the aim of building robust and human-centred AI systems for real-world deployment.