Short CV/Education and training

  • 1989 – 1990
    Attended Lyceum Nr. 1027 affiliated with the Moscow Power Engineering Institute – Technical University (MPEI), Russia

  • 1990 – 1996
    Studied at the Technical University MPEI in Moscow, qualified engineer and physicist, graduated with honours

  • 1996 – 1998
    Doctoral student at the Technical University MPEI

  • 1998 – 1999
    Visiting researcher at the University of Tübingen, Germany; Research project: Smart Fabrication – Neural Networks

  • 1999 – 2003
    Doctoral studies at the University of Tübingen: Dissertation: ART Fuzzy Classifiers: ART-based fuzzy networks for automatic classification

  • 2002 – 2006
    University of Tübingen: Doctoral student; starting in 2004, postdoc in the Research Training Group: Chemistry in interphases, project: EChem++

  • 2007 – 2008
    Parental leave

  • Since 2008
    University of Konstanz: Head of a young researcher group; project: DAMIART

Selected publications

  • Brucker, F. et al.: Multi-Label Classification and Extracting Predicted Class Hierarchies. Pattern Recognition, in press.

  • Benites, F. et al.: Multi-label Classification by ART-Based Neural Networks and Hierarchy Extraction. In: Proceedings of the IJCNN 2010. S. 2788-2796.

  • Sapozhnikova, E.: ART-Based Neural Networks for Multi-label Classification. In: Proceedings of the IDA 2009. S. 167-177.

  • Sapozhnikova, E. et al.: EChem++ – An object-oriented problem solving environment for electrochemistry. 3. Classification of voltammetric signals by the Fuzzy ARTMAP neural network with respect to reaction mechanisms. In: Journal of Electroanalytical Chemistry 588, 2006. S. 15-26.

  • Sapojnikova, E.: ART-based Fuzzy Classifiers: ART Fuzzy Networks for Automatic Classification. Cuvillier Verlag, Göttingen 2004.

Selected projects

  • Project DAMIART: Development of a data-mining system for heterogeneous data based on a neural network from the ART family

  • Project EChem++: Intelligent data analysis with neural networks for the automation of electrochemical experiments

  • Projects "Smart Fabrication – Neural Networks" and "Online Tool-Controlling with Neural Networks" (follow-up project); development of automatic methods of analysis based on artificial neural networks to be used in semiconductor manufacturing for quality control in order to discover malfunctions in the machines that produce the chip at an early stage


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