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Personal profile

Research interests

I work on advancing tools for human-centred data analysis. In contrast to machine learning methods that aim for automation (e.g., self-driving cars), human-centred data analysis methods aim to empower human users. In order to be effective, such methods and their results must be simple and interpretable yet provide valid answers to critical analysis questions.

I am interested in all aspects of data analysis methods: learning-theoretic foundations, efficient algorithms, and concrete applications. For the latter, I particularly focus on supporting scientific discoveries. For example, I collaborate with materials science researchers to pursue the data-driven discovery of novel functional materials.


  • Data Science
  • Data analysis
  • Machine Learning
  • Data mining

Research Output 2009 2011

  • 2 Article
  • 1 Conference Paper

Direct local pattern sampling by efficient two-step random procedures

Boley, M., Lucchese, C., Paurat, D. & Gärtner, T., 2011, 17th ACM SIGKDD International conference on knowledge discovery and data mining. p. 582-590

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Listing closed sets of strongly accessible set systems with applications to data mining

Boley, M., Horváth, T., Poigné, A. & Wrobel, S., 2010, In : Theoretical Computer Science. 411, 3, p. 691-700

Research output: Contribution to journalArticleResearchpeer-review

Approximating the number of frequent sets in dense data

Boley, M. & Grosskreutz, H., 2009, In : Knowledge and Information Systems. 21, 1, p. 65-89

Research output: Contribution to journalArticleResearchpeer-review


Best-Paper-Award ICDM 2018

Panagiotis Mandros (Recipient), Mario Boley (Recipient) & Jilles Vreeken (Recipient), 2018

Prize: Prize (including medals and awards)

Best-Student-Paper-Award ICDM 2008

Mario Boley (Recipient) & Henrik Grosskreutz (Recipient), 2008

Prize: Prize (including medals and awards)