Knowledge Management & Data Streams
- Devices & Data
- Knowledge Management & Data Streams
Presentation of research activities
The research of the Knowledge Management & Data Streams unit concerns in particular the development of knowledge pertaining to AI and the use of ontologies to represent patient information. This unit also works on different methods for the analysis and profiling of patient trajectory with the support of Machine Learning, on techniques managing sensor-generated data streams and other highly dynamic data sources, or also on behavioural change models and persuasion technology in the context of digital health applications.
Jean-Paul Calbimonte
Previously, Prof. Jean-Paul Calbimonte worked as a post-doc researcher within the LSIR EPFL, with Karl Aberer. He completed his PhD at the Universidad Politécnica of Madrid, focusing on the access to data based on data flow ontology under the supervision of Oscar Corcho. He also obtained a Master’s at the EPFL after a Bachelor’s at the UCB, Cochabamba. In addition, he did a brief stint in the industrial sector, working on medical information systems and application platforms in the field of radiology.
Prof. Calbimonte is an HES professor associated with the Applied Intelligent Systems Lab (AISLab) of the HES-SO Valais-Wallis. His main research work topics of interest are currently focusing on the application of AI and knowledge management techniques for their use in the field of health, and in particular the use of data semantics and machine learning techniques applied to data collected through wearables and detection devices. Some of the uses, for instance, concern chronic diseases, diabetes, active aging, and rehabilitation.
Route de la Plaine 2, Case postale 80
3960 Sierre
Switzerland
Partnership
Key publications
STKGNN: Scalable Spatio-Temporal Knowledge Graph Reasoning for Activity Recognition
Tataroğlu Özbulak, G. A., Shrestha, Y. R. & Calbimonte, J.-P. (2025).
Proc. Of the 34th ACM International Conference on Information and Knowledge Management CIKM, 2853–2862.
The ADVANCE toolkit: Automated descriptive video annotation in naturalistic child environments
Middelmann, N. K., Calbimonte, J.-P., Wake, E. B., Jaquerod, M. E., Junod, N., Glaus, J., Sidiropoulou, O., Plessen, K. J., Murray, M. M. & Vowels, M. J. (2025).
Behavior Research Methods, 58(1).
Grounding Stream Reasoning Research. Transactions on Graph Data and Knowledge
Bonte, P., Calbimonte, J.-P., de Leng, D., Dell’Aglio, D., Della Valle, E., Eiter, T., Giannini, F., Heintz, F., Schekotihin, K., Le-Phuoc, D., Mileo, A., Schneider, P., Tommasini, R., Urbani, J. & Ziffer, G. (2024).
2(1), 2:1–2:47.
Dynamic Swarm Orchestration and Semantics in IoT Edge Devices: A Systematic Literature Review
Anuraj, B., Calvaresi, D., Aerts, J.-M. & Calbimonte, J.-P. (2024).
IEEE Access, 12, 116917–116938.
Early diagnosis of Alzheimer’s disease and mild cognitive impairment using MRI analysis and machine learning algorithms
Givian, Helia and Calbimonte, Jean-Paul and and for the Alzheimer’s Disease Neuroimaging Initiative. (2024).
Discover Applied Sciences, 7(1), 27.
Breast cancer survival analysis agents for clinical decision support
Manzo, G., Pannatier, Y., Duflot, P., Kolh, P., Chavez, M., Bleret, V., Calvaresi, D., Jimenez del Toro, O., Schumacher, M. & Calbimonte, J.-P. (2023).
Computer Methods and Programs in Biomedicine, 231, 107373.