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Dr Stephen Kahara Wanjau

Dr Stephen Kahara Wanjau

Lecturer: School of Computing & Information Technology
skahara@mut.ac.ke

Google Scholar: https://scholar.google.com/citations?hl=en&user=JYqVThgAAAAJ

Research Gate : https://www.researchgate.net/profile/Stephen-Wanjau-3

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Biography

Dr. Stephen Kahara is a seasoned ICT professional and academic with over fifteen years of experience and a strong academic foundation, holding a Ph.D. in Computer Science. Currently serving as a Lecturer in the Computer Science Department and Director of Performance Contracting and ISO at Murang’a University of Technology, Dr. Kahara brings a wealth of expertise in strategic leadership, process improvement, and project management. As a trained auditor of QMS and ISMS management systems and an alumnus of the DAAD-supported UNILEAD program, he excels in bridging theoretical knowledge with practical application. His research interests span machine learning, network security, distributed systems, and computational biology, reflected in his authored journal articles, book chapters, and conference papers. A member of the Association of Computing Practitioners – Kenya (ACPK), Dr. Kahara is passionate about leveraging technology for innovation and organizational efficiency. His proficiency in data management, analytics, and risk management, combined with his academic rigor and industry insight, positions him as a valuable asset in both educational and professional spheres.

Education

  • 2019-2023: Doctor of Philosophy in Computer Science- Murang’a University of Technology
  • 2013-2018: Master of Science in Computer Systems- Jomo Kenyatta University of Agriculture and Technology
  • 2009-2010: Executive Master of Science in Organizational Development

Publications

  1. K. Wanjau, G. M. Wambugu, A. M. Oirere, Evaluating Linear and Non-LinearDimensionality Reduction Approaches for Deep Learning-based Network Intrusion Detection Systems, International Journal of Wireless and Microwave Technologies (IJWMT), vol.13, no.4 https://doi.org/10.5815/ijwmt.2023.04.05
  2. Wanjau, S.K. , Mariga, G. M. & Oirere A.M. (2022). Network Intrusion Detection Systems: A Systematic Literature Review of Hybrid Deep Learning Approaches. International Journal of         Emerging         Science         and            Engineering                  (IJESE),      10(7),      1-16.      https://doi.org/10.35940/ijese.F2530.0610722.
  3. Wanjau, S. K., Wambugu, G. M., Oirere, A. M. and Muketha, G.M. Discriminative Spatial- Temporal Feature Learning for Modeling Network Intrusion Detection Systems, Journal of Computer Security, vol. Pre-press, no. Pre-press, pp. 1-30, 2023. https://doi.org/10.3233/JCS-220031
  4. Wanjau, S., Mariga, G. & Kamau, G. (2021). SSH-Brute Force Attack Detection Model based on Deep Learning. International Journal of Computer Applications Technology and Research, 10(1), 42-50. ISSN: 2319-8656.
  5. Wanjau, S., & Muketha, G. (2018). Improving Student Enrollment Prediction Using Ensemble Classifiers. International Journal of Computer Applications Technology and Research, 7(3), 122-128. ISSN: 2319-8656.
  6. Wanjau, S., Okeyo, G., & Rimiru, R. (2016). Data Mining Model for Predicting Student Enrolment in STEM Courses in Higher Education Institutions. International Journal of Computer Applications Technology and Research, 5(11), 698-704. ISSN: 2319-8656.

Book Chapter

  1. Wanjau, S.K., & Muketha, G.M. (2021). A Novel Hybrid Deep Learning Model for Early Detection of Diabetic Retinopathy. In Amutabi, M.N.(Ed.), New Trends of Global Influences in Africa (pp. 73-89). CEDRED Publications, Nairobi, Kenya. ISBN 978-9966-116-55-0
  2. Wanjau, S. K. (2020). Enterprise Resource Planning System Implementation in Higher Education Institutions: A Theoretical Review. In G. Muketha, & E. Micheni (Eds.), Metrics and Models for Evaluating the Quality and Effectiveness of ERP Software (pp. 236-264). Hershey, PA: IGI Global. https://doi.org/10.4018/978-1-5225-7678-5.ch010