Juha Harviainen earned his PhD in computer science in 2024 from the University of Helsinki under the supervision of Prof. Mikko Koivisto. Following his doctoral studies, he continued as a postdoctoral researcher in Prof. Koivisto's group Sums of Products through 2025. In January 2026, he started as an HIIT Postdoctoral Fellow in the Graph Algorithms and Bioinformatics research group, led by Prof. Alexandru I. Tomescu at the University of Helsinki.
Harviainen’s research focuses on designing more efficient algorithms in various settings such as bioinformatics and artificial intelligence by exploiting the structural properties of problem instances, with a particular emphasis on parameterized complexity. His other research interests include counting problems, randomized algorithms, and fine-grained complexity theory.
Sample of Publications
[1] Juha Harviainen, Frank Sommer, Manuel Sorge, Stefan Szeider. 2025. Optimal Decision Tree Pruning Revisited: Algorithms and Complexity. Proceedings of the Forty-Second International Conference on Machine Learning (ICML 2025).
[2] Juha Harviainen, Pekka Parviainen. 2025. On Tractability of Learning Bayesian Networks with Ancestral Constraints. Proceedings of the Twenty-Eighth International Conference on Artificial Intelligence and Statistics (AISTATS 2025).
[3] Juha Harviainen, Mikko Koivisto. 2024. Estimating the Permanent by Nesting Importance Sampling. Proceedings of the Forty-First International Conference on Machine Learning (ICML 2024).