Mr. David Ndumiyana

  • MSc. Computer Science (UZ)
  • BSc. Mathematics and Computer Science (CUBA)

Research Interests

  • E-learning
  • Mobile learning
  • Artificial intelligence and expert systems


  1. Ndumiyana, D. and Mukabeta, T., 2017. Behaviour-based malware classification on mobile phones using support vector machines.
  2. Ndumiyana, D.,Sakala, L.C. (2013). Hidden Markov Models and Artificial Neural networks for spam detection. International Journal of Engineering Research and Technology.2(4),2069-2084
  3. Ndumiyana, D., Magomelo, M., Sakala, L. (2013). Spam detection using a neural network classier. Journal of Physical and Environmental Research, 2(2), 28-37.
  4. Ndumiyana, D., Gotora, R., Mupamombe, T. (2013). Spam detection using adaptive neural networks: Adaptive resonance theory. Journal of Physical and
  5. Ndumiyana, D., Gotora, R., Chikwiriro, H. (2013). Data mining techniques in intrusion detection: Tightening network security. International Journal of Engineering Research and Technology, 2(5), 2237-2248