Mr Jackson Kamiri Wambugu

School of Computing & Information Technology

jkamiri@mut.ac.ke

Google Scholar: https://scholar.google.com/citations?user=LU4sVRoAAAAJ&hl=en&authuser=1

Research Gate : https://www.researchgate.net/profile/Jackson-Kamiri

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Biography

Jackson Kamiri is a Tutorial Fellow in the department of Information Technology, School of Computing and Information Technology. He joined the department in November 2019 as a Graduate Assistant and steadily rose through the ranks, earning a promotion to Tutorial Fellow in 2023. Kamiri holds a Master of Science in Information Technology (2022) and a Bachelor of Business Information Technology- First Class Honours (2019) from Murang’a University of Technology. He is currently pursuing Doctor of Philosophy in Information Technology. His research interests are in the field of Artificial Intelligence (A.I), the subfield of deep learning. He has published widely in this area and his work can be accessed in the University repository or Google Scholar profile.

Education

2023-ONGOING- Doctor of Philosophy in Information Technology- Murang'a University of Technology
2020-2022: Master of Science in Information Technology- Murang'a University of Technology
2015-2019: Bachelor of Business Information Technology- Murang’a University of Technology

Publications

Kamiri and G. Mariga, “Research Methods in Machine Learning: A Content Analysis”, IJCIT, vol. 10, no. 2, Mar. 2021, https://doi.org/10.24203/ijcit.v10i2.79.
Kamiri, G. Mariga, and A. Oirere, “A Systematic Literature Review of Meta-Learning Models for Classification Tasks,” Int. J. Comput. Appl. Technol. Res., vol. 11, no. 03, pp. 56–65, 2022, https://doi.org/10.7753/ijcatr1103.1002.
Kamiri, G. M. Wambugu, and A. M. Oirere, “A Comparative Study of Deep Learning and Transfer Learning in Detection of Diabetic Retinopathy,” Int. J. Comput. Appl. Technol. Res., vol. 11, no. 07, pp. 247–254, 2022, https://doi.org/10.7753/ijcatr1107.1001.
Onyango, A., Kamiri, J., & Muketha, G. M. (2023). A comparative study of the lexicographical complexity of Java, Python and C languages based on program characteristics. Journal of Innovation, Technology and Sustainability, 1(1), 42-67.