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Dr. Alexander Munteanu

Mathematische Statistik und biometrische Anwendungen


Mathematics Building,
Room E16b
+49 231 755 - 7885
+49 231 755 - 5303
Fakultät Statistik
Technische Universität Dortmund
44221 Dortmund

Research interests

I am mainly interested in the design and analysis of algorithms for tackling the challenges of massive data and high dimensionality. I am also interested in collaborating on possible applications. My research involves several scientific fields such as

  • streaming and distributed algorithms,
  • randomized linear algebra,
  • machine learning,
  • computational statistics,
  • computational geometry,
  • convex optimization.
  • Publications


    • Leo N. Geppert, Katja Ickstadt, Alexander Munteanu, Christian Sohler.
      Streaming statistical models via Merge & Reduce.
      International Journal of Data Science and Analytics, 10(4):331-347, 2020.


    • Stefan Meintrup, Alexander Munteanu, Dennis Rohde.
      Random projections and sampling algorithms for clustering of high-dimensional polygonal curves.
      Advances in Neural Information Processing Systems (NeurIPS), 2019.
    • Alexander Munteanu, Amin Nayebi, Matthias Poloczek.
      A framework for Bayesian optimization in embedded subspaces.
      International Conference on Machine Learning (ICML), 2019.
    • Amer Krivosija, Alexander Munteanu.
      Probabilistic smallest enclosing ball in high dimensions via subgradient sampling.
      Symposium on Computational Geometry (SoCG), 2019.
      European Workshop on Computational Geometry (EuroCG), 2019.


    • Alexander Munteanu, Chris Schwiegelshohn, Christian Sohler, David Woodruff.
      On coresets for logistic regression.
      Advances in Neural Information Processing Systems (NeurIPS), 2018.
    • Alexander Munteanu.
      On large-scale probabilistic and statistical data analysis.
      PhD Thesis. Technische Universität Dortmund, 2018.
    • Kristian Kersting, Alejandro Molina, Alexander Munteanu.
      Core dependency networks.
      AAAI Conference on Artificial Intelligence (AAAI), 2018.
    • Alexander Munteanu, Chris Schwiegelshohn.
      Coresets - methods and history: a theoreticians design pattern for approximation and streaming algorithms.
      KI special issue on "Algorithmic Challenges and Opportunities of Big Data", 32(1):37-53, 2018.


    • Leo N. Geppert, Katja Ickstadt, Alexander Munteanu, Jens Quedenfeld, Christian Sohler.
      Random projections for Bayesian regression.
      Statistics and Computing, 27(1):79-101, 2017.


    • Alexander Munteanu, Max Wornowizki.
      Correcting statistical models via empirical distribution functions.
      Computational Statistics, 31(2):465-495, 2016.


    • Dan Feldman, Alexander Munteanu, Christian Sohler.
      Smallest enclosing ball for probabilistic data.
      Symposium on Computational Geometry (SoCG), 2014.
    • Marc Heinrich, Alexander Munteanu, Christian Sohler.
      Asymptotically exact streaming algorithms.
      ArXiv preprint, CoRR abs/1408.1847, 2014.


    My interdisciplinary teaching activities are listed below. Students interested in Bachelor's or Master's theses in either Computer Science, Statistics, or Data Science may contact me anytime via email. Office hours only by appointment.