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Tanja Hagemann, M.Sc.

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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 T-Labs in the area of Future Networks & AI, 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

Publications

Motta, M. and Hagemann, T. and Fischer, S. and Assion, F. (2021). EvolMusic: Towards Musical Adversarial Examples for Black-Box Attacks on Speech-To-Text. 2021 Genetic and Evolutionary Computation Conference Companion (GECCO ’21 Companion), accepted for publication


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 zur Publikation

Hagemann, T. and Katsarou, K. (2020). A Systematic Review on Anomaly Detection for Cloud Computing Environments. 3rd Artificial Intelligence and Cloud Computing Conference (AICCC 2020). ACM, 83-96.

Link zur Publikation

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.


Anomaly Detection with HMM Gauge Likelihood Analysis
Zitatschlüssel lorbeer2019anomaly
Autor Lorbeer, B. and Deutsch, T. and Ruppel, P. and Küpper, A.
Buchtitel 2019 IEEE Fifth International Conference on Big Data Computing Service and Applications (BigDataService)
Seiten 1–8
Jahr 2019
Organisation IEEE
Typ der Publikation SNET Data
Download Bibtex Eintrag

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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