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Prof Stephen Gbenga Fashoto

Associate Professor


Phone : +264 83 207 2395 /+264 61 207 2395
Email : sfashoto@nust.na

Qualification
Ph.D. Computer Science (UNILORIN)
M.Sc. Computer Science (UNIPORT)
B.Sc. (Hons) Comp. Sc. And Maths (UNIPORT)


Research Interest : Data Science, Data Mining, Machine Learning, Health Informatics, AI and Explainable AI

Prof. Stephen Gbenga Fashoto‬ - ‪Google Scholar‬

 

Selected Publications

Fashoto, S.G., Faremi, A.S., Mbunge, E., & Owolabi, O. (2024). Exploring structural equations modelling on the use of modified UTAUT model for evaluating online learning. Educational Technology Quarterly, Volume 2024, No. 3

 

Fashoto, S.G., Akinnuwesi, B.A., Mbunge, E. & Metfula, A.S. (2023). Financial inclusion dataset  classification in Eswatini using support vector machine and logistic regression International. Journal of Business Information Systems, Vol. 43, No. 4, pp.507–527 Inderscience

 

Govender, P, Fashoto, SG, Maharaj, L, Adeleke, MA, Mbunge, E, Olamijuwon, J, & Okpeku, M. (2022). The application of machine learning to predict genetic relatedness using human mtDNA hypervariable region I sequences. Plos One, Vol. 17(2), e0263790

 

Fashoto, SG & Sani, S. (2021). Design and Implementation of MOLP Problems with Fuzzy Objective Functions Using Approximation and Equivalence Approach. International Journal of Computer Science (IAENG).

 

Fashoto, SG, Mbunge, E., Ogunleye, AO & Van den Burg, J. (2021). Implementation of machine learning for predicting maize crop yields using multiple linear regression and backward elimination. Malaysia Journal of Computing, Vol. 6, Issue 1, pp. 679-697

 

Elujide, OI, Fashoto, SG, Fashoto, OY, Mbunge, E, Folorunso, SO & Olamijuwon, JO (2021). Application of deep and machine learning techniques for multi-label classification performance on psychotic disorder diseases. Informatics in Medicine Unlocked, Vol, 23,

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