HIIT Postdoctoral Fellow 1.1.2023-31.05.2026
Florian Adriaens received his PhD degree in 2020 at Ghent University as a member of the Artificial Intelligence & Data Analytics Group led by Prof. Tijl De Bie, and co-supervised by Prof. Jefrey Lijffijt. After graduating he worked for two years as a postdoctoral researcher in KTH University in the data mining group of Prof. Aristides Gionis. Since January 2023 Florian started working as a HIIT postdoctoral fellow under the supervision of Prof. Nikolaj Tatti.
His broad research interests include graph algorithms, social-network analysis and graph mining. His current research is focused on algorithm design for computational problems related to polarization and distance reduction in social networks.
Sample of recent publications:
[1] Florian Adriaens, Nikolaj Tatti. 2025. Fair Diversity Maximization with Few Representatives. In KDD '25: Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining V.2 (pp. 17-25). ACM.
[2] Vedangi Bengali, Nikolaj Tatti, Iiro Kumpulainen, Florian Adriaens & Nate Veldt. 2025. The Densest SWAMP Problem: Subhypergraphs with Arbitrary Monotonic Partial Edge Rewards. In: Ribeiro, R.P., et al. Machine Learning and Knowledge Discovery in Databases. Research Track. ECML PKDD 2025. Lecture Notes in Computer Science(), vol 16015.