TU Berlin

Service-centric NetworkingBoris Lorbeer

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Boris Lorbeer

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After receiving a diploma in Physics from Technische Universität Berlin, Boris Lorbeer worked for a couple of companies as software developer and data scientist. He soon specialized in machine learning, which he applied to e.g. prediction analysis, pattern recognition, anomaly detection, text analysis, ad click optimization or computer vision.

In May 2015, Boris Lorbeer joined the Telekom Innovation Laboratories as a research scientist in the strategic research area of Service-centric Networking led by Prof. Dr. Axel Küpper. His research interests include machine learning, deep learning, discrete geometry and graph theory and the application of those fields to networking.

Research Interests

  • Machine Learning
  • Deep Learning
  • Discrete Geometry
  • Graph Theory

Publications

Lorbeer, B. and Deutsch, T. and Ruppel, P. and Küpper, A. (2019). Anomaly Detection with HMM Gauge Likelihood Analysis. BDS2019 accepted for publication.


Lorbeer, B. and Kosareva, A. and Deva, B. and Softić, D. and Ruppel, P. and Küpper, A. (2017). Variations on the Clustering Algorithm BIRCH. Big Data Research. Elsevier.


Lorbeer, B. and Kosareva, A. and Deva, B. and Softić, Dvzenan and Ruppel, P. and Küpper, Axel (2016). A-BIRCH: Automatic Threshold Estimation for the BIRCH Clustering Algorithm. A-BIRCH: Automatic Threshold Estimation for the BIRCH Clustering Algorithm. Springer, 169–178.

Link to publication

Thesis

  • Lorbeer, B. (1995). The Einstein field equations as an infinite dimensional Hamiltonian system.  Diploma Thesis, Technische Universität Berlin

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