Shahrooz Abghari
Senior Lecturer
Department of Computer Science
Room J3126, Karlskrona
Research domain: Computer Science
Dr. Shahrooz Abghari is a lecturer in the Computer Science Department at Blekinge Institute of Technology (BTH), where he pursued his Ph.D. His main research interests and activities revolve around outlier (anomaly) detection. Shahrooz mainly works with the industry on different application domain problems and challenges. Regarding research experience, he primarily focuses on data analysis, unsupervised machine learning and data mining techniques, and time series analysis. Shahrooz did his Ph.D. under BigData@BTH, a six-year research project (2014-2020) founded by the Knowledge Foundation, BTH, and eight company partners. He was a research team member in Distributed and Adaptive Edge-based AI Models for Sensor Networks project in collaboration with SONY R&D Lund Center (2021-2022). Shahrooz is currently a research team member in HINTS – Human-Centered Intelligent Realities, a six-year (2022-2028) BTH research project co-funded by the Knowledge Foundation Research Profiles program.
Latest publications
- Veselka Boeva, Alexander Ojutkangas, Shahrooz Abghari, "Multi-view Multi-instance Learning for Health Recovery Monitoring in Older Adults", Communications in Computer and Information Science, ISSN 1865-0929, EISSN 1865-0937, pp. 398-411, Springer Science+Business Media B.V., 2026
- Tharuka Kasthuri Arachchige, Veselka Boeva, Shahrooz Abghari, "FedABoost", Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ISSN 1865-0929, EISSN 1865-0937, pp. 1-16, Springer Nature, 2026
- Milena Angelova, Veselka Boeva, Shahrooz Abghari, Selim Ickin, Xiaoyu Lan, "FedCluLearn", Machine Learning and Knowledge Discovery in Databases. Research Track, ECML PKDD 2025, PT II, ISSN 0302-9743, EISSN 1611-3349, pp. 331-349, Springer Science+Business Media B.V., 2026
- Valeria Garro, Ilir Jusufi, Shahrooz Abghari, Jens Brage, Veselka Boeva, "Exploring Dynamic Hypergraphs for Clustering Analysis of District Heating Data", 18th International Symposium on Visual Information Communication and Interaction, VINCI 2025, Association for Computing Machinery (ACM), 2025
- Selim Ickin, Xiaoyu Lan, Milena Angelova, Shahrooz Abghari, Veselka Boeva, "Sample Selection Methods for Federated Continual Learning in a Time Series Context", IEEE Access, EISSN 2169-3536, Vol. 13, pp. 189057-189073, Institute of Electrical and Electronics Engineers (IEEE), 2025
Completed projects
No information available