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Vitali Herrera Semenets (vherrera)

Contact Info

Vitali Herrera Semenets (vherrera)


Research Topics of Interest

His research interests include but not restricted to:

  • Data Reduction.
  • Automatic Rule Generation in Data Streams.
  • Malicious Activities Detection.


  • Member of the Cuban Association for Pattern Recognition (www.acrp.cenatav.co.cu)
  • Member of the Cuban Society of Mathematics and Computing (SCMC)
  • Member of the Union of Cuban Informatics (UIC)

Academic Background

  • Engineer of Computer Sciences. University of Informatic Sciences, Cuba, July 2009.

Academic Experience

Guest Researcher

  • Delft University of Technology. Department of Intelligent Systems. Cyber Security Group. Netherlands, Delft, South Holland

BSc. Students

  • Mario Alfonso Prado Romero (Dissertation in June, 2013) [In conjuntion with Dr. Andrés Gago-Alonso]. Graduated in Computer Science at UH. Thesis topic: A Framework for Fraud Detection in Communication Networks.


  1. Herrera-Semenets, V., Febrer-Hernandez, J. K.: TASK MANAGER FOR DISTRIBUTED PROCESSING OF DATA STREAM. IX International Congress of Mathematics and Computing. La Habana, Cuba, 2017. 
  2. Herrera-Semenets, V., Perez-Garcıa, O. A., Hernandez-Leon, R. An ensemble based feature selection strategy and its application to intrusion detection. International Conference on Information Processing (CIPI 2017). Matanzas, Cuba, 2017.
  3. Herrera-Semenets, V., Perez-Garcıa, O. A., Gago-Alonso, A., Hernandez-Leon, R. Classification rule-based models for malicious activity detection. Intelligent Data Analysis Vol. 21, No. 5, pp. 1141–1154, 2017. 
  4. V. Herrera-Semenets, A. Gago-Alonso. A novel rule generator for intrusion detection based on frequent subgraph mining. Ingeniare. Revista chilena de ingeniería. ISSN: 0718-3305, Vol. 25, No. 2, pp. 226-234, 2017. [pdf]
  5. V. Herrera-Semenets, A. Gago-Alonso. Modelos basados en reglas de clasificación para la detección de actividades maliciosas. Technical Report RT_35. Serie Gris, Advanced Technologies Application Center, La Habana, Cuba. Julio, 2016. [pdf]
  6. V. Herrera-Semenets, A. Gago-Alonso, O. A. Pérez-García. Plataforma Eficiente para Detectar Actividades Maliciosas utilizando Grafos. III Conferencia Internacional en Ciencias Computacionales e Informáticas (CICCI 2016). Informática 2016, La Habana, Cuba.
  7. V. Herrera-Semenets, N. Acosta-Mendoza, A. Gago-Alonso. A Framework for Intrusion Detection based on Frequent Subgraph Mining. In proceedings of The Second SDM Workshop on Mining Networks and Graphs: A Big Data Analytic Challenge (SDM-Networks 2015). In conjunction with 2015 SIAM international Conference on Data Mining (SDM15), Vancouver, BC, Canada, May, 2015. ISSN 2167‐0099
  8. V. Herrera-Semenets, A. Gago-Alonso. Búsqueda automática de reglas para detección de fraudes en flujos de eventosTechnical Report RT_29. Serie Gris, Advanced Technologies Application Center, La Habana, Cuba. Enero, 2015. [pdf]
  9. V. Herrera-Semenets, M.A. Prado-Romero, A. Gago-Alonso. Análisis de los métodos de detección de fraude en servicios de telecomunicacionesTechnical Report RT_23. Serie Gris, Advanced Technologies Application Center, La Habana, Cuba. Febrero, 2014. [pdf]


Pattern Recognition Department
Data Mining Department
Biometric Department