Pauli Miettinen
Professor of Data Science
Email:
pauli.miettinen@uef.fi
Phone: +358 2 9445 3410
Fax: +358 2 9445 7318
Who am I?
I am a professor of data science at UEF's School of Computing, at Kuopio campus. Formerly I was a senior researcher at Max Planck Institute for Informatics in Saarbrücken, Germany. I am also a docent (adjunct professor) at University of Helsinki.
I study algorithmic data analysis, and I am interested to both theory and applications thereof. I lead the Algorithmic Data Analysis research group at UEF. My main research has been in the fields of Boolean and (sub-) tropical matrix and tensor factorizations, redescription mining, and social network analysis. You can find my publications in my Publications page.
What's new
- Our paper Brain Ventricle Morphology Markers in Predicting Shunt Surgery Outcome in Idiopathic Normal-Pressure Hydrocephalus has been accepted for publication in Fluids and Barriers of the CNS
- Ryan Wood joins the group as a post-doc in Research Council Finland funded PAPADAM-project. Welcome!
- Maiju Karjalainen defended her thesis Trading Accuracy for Privacy and Speed in Pattern Mining on 24 October 2025. Opponent was Prof. Dr. Jilles Vreeken from CISPA Helmholtz Center for Information Security and Saarland University. Congratulations!
- Jonne Klockars joins the group as a PhD student in Research Council Finland funded PAPADAM-project. Welcome!
- Our paper Hashing for Fast Pattern Set Selection will appear in ECML PKDD 2025
- Research Council Finland funds the PAPADAM-project, co-PIs me and Nikolaj Tatti from University of Helsinki
- Interesting abstracts from interesting Dagstuhl seminar here.
- Two worlds collide: our work using NMF to describe redescriptions has appeared in IEEE TKDE.
- Charmin Asirimath joins the group as a part of the Finnish Doctoral Program Network in Artificial Inteligence (AI-DOC). Welcome!
- Ambre Ayats joins the group as a YUFE postdoc. Welcome!
- How to mine redescriptions faster than before? Check out the new paper to appear at ECML PKDD!
Recent publications
- Brain Ventricle Morphology Markers in Predicting Shunt Surgery Outcome in Idiopathic Normal-Pressure Hydrocephalus. Fluids and Barriers of the CNS, 2026
-
Hashing for Fast Pattern Set Selection.
Proc. ECML PKDD,
,
129–146.
10.1007/978-3-032-06096-9_8
[manuscript | pdf (Springer) | tech. rep. | source code] -
Hashing for Fast Pattern Set Selection.
arXiv:2507.08745 [cs.DB]
.
10.48550/arXiv.2507.08745
[pdf (arXiv) | source code] -
Hyperbolic Communities: Modelling Communities Beyond Cliques.
Statistical and Probabilistic Methods in Algorithmic Data Analysis (Dagstuhl Seminar 24391)
14(9),
,
136.
10.4230/DagRep.14.9.127
[pdf (Schloss Dagstuhl)] -
Finding Rule-Interpretable Non-Negative Data Representation.
IEEE Transactions on Knowledge Discovery and Data Mining
37(5),
,
2538–2549.
10.1109/TKDE.2025.3538327
[ pdf (IEEE) | tech. rep. | source code] -
Fast Redescription Mining Using Locality-Sensitive Hashing.
Proc. ECML PKDD,
,
124–142.
10.1007/978-3-031-70368-3_8
[manuscript | tech. rep. | source code] -
Fast Redescription Mining Using Locality-Sensitive Hashing.
arXiv:2406.04148 [cs.LG]
.
10.48550/arXiv.2406.04148
[pdf (arXiv) | source code] -
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations.
Proc. ECML PKDD,
,
743–758.
10.1007/978-3-031-43412-9_44
[manuscript | pdf (Springer) | tech. rep. | source code] -
Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations.
arXiv:2307.07396 [cs.LG]
.
10.48550/arXiv.2307.07396
[pdf (arXiv)] -
Differentially Private Tree-Based Redescription Mining.
Data Mining and Knowledge Discovery
37(4)
,
1548–1590.
10.1007/s10618-023-00934-8
[pdf (Springer) | tech. rep. | source code] -
Serenade: An Approach for Differentially Private Greedy Redescription Mining.
Proc. 20th Anniversary Workshop on Knowledge Discovery in Inductive Databases,
,
31–46.
[manuscript | pdf (CEUR-WS) | source code]