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Dr. Alexander Munteanu

Contact data
Address Dekanat Statistik - Dortmund Data Science Center
Technische Universität Dortmund
Vogelpothsweg 87
44227 Dortmund
Germany
Office Campus Nord, Mathematics Building, Room E16b
Phone +49 231 755-7885
Fax +49 231 755-5303
Email alexander.munteanu(at)tu-dortmund.de
Alexander

About me: After receiving my PhD in theoretical computer science under supervision of Christian Sohler, I am now postdoctoral researcher at the Statistics department of TU Dortmund in the group led by Katja Ickstadt.
I am principle investigator in a joint project on large-scale and high-dimensional regression problems within the collaborative research center SFB 876 and I am happy to advise Simon Omlor as my first PhD student.
Last but not least, I am happy to help building up the Dortmund Data Science Center in the position of its managing director.

Research Interests: I am mainly interested in the design and analysis of algorithms for tackling the challenges of massive data and high dimensionality.
This involves several fields of research such as streaming and distributed algorithms, randomized linear algebra,
machine learning, computational statistics, computational geometry, convex optimization.
I am also interested in collaborating on possible applications.

Teaching: My interdisciplinary teaching activities can be found in the bottom of this page. Students interested in Bachelor's or Master's theses in either Computer Science, Statistics, or Data Science may contact me anytime via e-mail. Office hours only by appointment.


Publications

2020

  • 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.

2019

  • 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.

2018

  • 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.

2017

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

2016

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

2014

  • 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.

Teaching