Scaling Up Bayesian DAG Sampling, 2025, arXiv preprint
Improving Decision Trees through the Lens of Parameterized Local Search, NeurIPS 2025 (to appear)
Graph Reconstruction with the Connected Components Oracle, 2025, arXiv preprint
Quantum Speedups for Bayesian Network Structure Learning, UAI 2025
Optimal Decision Tree Pruning Revisited: Algorithms and Complexity, ICML 2025
On Tractability of Learning Bayesian Networks with Ancestral Constraints, AISTATS 2025
Estimating the Permanent by Nesting Importance Sampling, ICML 2024
Faster Perfect Sampling of Bayesian Network Structures, UAI 2024
Revisiting Bayesian Network Learning with Small Vertex Cover, UAI 2023
On Inference and Learning With Probabilistic Generating Circuits, UAI 2023
A Faster Practical Approximation Scheme for the Permanent, AAAI 2023
Trustworthy Monte Carlo, NeurIPS 2022
Approximating the Permanent with Deep Rejection Sampling, NeurIPS 2021
Software Framework for Data Fault Injection to Test Machine Learning Systems, ISSRE Workshops 2019
Research Experience
Works as a postdoctoral researcher in the Sums of Products research group.
Education
Completed his doctoral degree in 2024 under the supervision of Professor Mikko Koivisto at the University of Helsinki.
Background
Currently a postdoctoral researcher at the University of Helsinki, focusing on parameterized complexity, perfect sampling, and having a broader interest in randomized algorithms, complexity theory, and information theory.
Miscellany
Created a website called Tie koodariksi for teaching programming in Finnish schools.