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TU Berlin

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Tanja Hagemann, M.Sc.


Tanja Hagemann is an external research assistant and PhD candidate at Service-centric Networking. In 2016 she achieved her Master's degree in mathematics at Wuppertal University with a focus on stochastic processes and multi-dimensional, complex analysis.

Besides her studies she gained versatile experience in data science and applied statistics during projects in a market research institute, at DLR Neustrelitz and at Wuppertal Institute for Climate, Environment and Energy. 

At SNET she is responsible for the research project ALMA which aims to improve the maintenance of cloud-based infrastructures through machine learning and deep learning. Her further research is in cooperation with the Intelligence Team at Telekom Innovation Laboratories, where she is involved in the research and development of machine learning solutions for Deutsche Telekom.

Research Interests

  • Data Science
  • Machine Learning
  • Deep Learning
  • Anomaly Detection
  • Statistical Learning Theory
  • Applied Statistics
  • Probability Theory
  • Stochastic Analysis


Hagemann, T. and Katsarou, K. (2020). Reconstruction-based anomaly detection for the cloud: A comparison on the Yahoo!Webscope S5 dataset. 4th International Conference on Cloud and Big Data Computing(ICCBDC 2020). ACM, 68-75.

Link to publication

Hagemann, T. and Katsarou, K. (2020). A Systematic Review on Anomaly Detection for Cloud Computing Environments. 3rd Artificial Intelligence and Cloud Computing Conference (ISNCC 2020). ACM (accepted for publication).

Victor, F. and Hagemann, T. (2019). Cryptocurrency Pump and Dump Schemes: Quantification and Detection. 2019 IEEE International Conference on Data Mining Workshops (ICDMW), 244–251.

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

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Tanja Hagemann M.Sc.
Service-centric Networking
TEL 19
Ernst-Reuter-Platz 7
10587 Berlin
Phone: +49 30 8353-58337
Fax: +49 30 8353 58409