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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

• 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!
• Ever wondered how a Boolean matrix factorization looks like? Wonder no more!
• How to mine differentially private redescriptions with a greedy algorithm? What about differentially private tree-based redescriptions? Check out our new papers!
• The 21st IEEE International Conference on Data Mining (ICDM) will be held in Auckland, NZ (or online) and the organisation is looking strong!

Recent publications

• Pauli Miettinen Hyperbolic Communities: Modelling Communities Beyond Cliques. Statistical and Probabilistic Methods in Algorithmic Data Analysis (Dagstuhl Seminar 24391) 14(9), 2025, 136.
  10.4230/DagRep.14.9.127
  [pdf (Schloss Dagstuhl)]
• Matej Mihelčić Pauli Miettinen Finding Rule-Interpretable Non-Negative Data Representation. IEEE Transactions on Knowledge Discovery and Data Mining 37(5), 2025, 2538–2549.
  10.1109/TKDE.2025.3538327
  [ pdf (IEEE) | tech. rep. | source code]
• Maiju Karjalainen Esther Galbrun Pauli Miettinen Fast Redescription Mining Using Locality-Sensitive Hashing. Proc. ECML PKDD, 2024, 124–142.
  10.1007/978-3-031-70368-3_8
  [manuscript | tech. rep. | source code]
• Maiju Karjalainen Esther Galbrun Pauli Miettinen Fast Redescription Mining Using Locality-Sensitive Hashing. arXiv:2406.04148 [cs.LG] 2024.
  10.48550/arXiv.2406.04148
  [pdf (arXiv) | source code]
• Thibault Marette Pauli Miettinen Stefan Neumann Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations. Proc. ECML PKDD, 2023, 743–758.
  10.1007/978-3-031-43412-9_44
  [manuscript | pdf (Springer) | tech. rep. | source code]
• Thibault Marette Pauli Miettinen Stefan Neumann Visualizing Overlapping Biclusterings and Boolean Matrix Factorizations. arXiv:2307.07396 [cs.LG] 2023.
  10.48550/arXiv.2307.07396
  [pdf (arXiv)]
• Matej Mihelčić Pauli Miettinen Differentially Private Tree-Based Redescription Mining. Data Mining and Knowledge Discovery 37(4) 2023, 1548–1590.
  10.1007/s10618-023-00934-8
  [pdf (Springer) | tech. rep. | source code]
• Maiju Karjalainen Esther Galbrun Pauli Miettinen Serenade: An Approach for Differentially Private Greedy Redescription Mining. Proc. 20th Anniversary Workshop on Knowledge Discovery in Inductive Databases, 2023, 31–46.
  [manuscript | pdf (CEUR-WS) | source code]
• Matej Mihelčić Pauli Miettinen Differentially Private Tree-Based Redescription Mining. arXiv:2212.06630 [cs.DB] 2022.
  10.48550/arXiv.2212.06630
  [pdf (arXiv)]
• Matej Mihelčić Pauli Miettinen Finding Rule-Interpretable Non-Negative Data Representation. arXiv:2206.01483 [cs.LG] 2022.
  10.48550/arXiv.2206.01483
  [pdf (arXiv)]

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