Dr. Mahenge

Dr. Michael P. J. Mahenge


Academic Profile

Michael P. J. Mahenge is a lecturer from the Sokoine University of Agriculture (SUA), Tanzania and coordinator for research and publication unit at the department of Informatics and Information Technology (DIIT), College of Natural and Applied Sciences (CoNAS). He pursued a PhD in Computer Science and Technology from Wuhan University of Technology, China, 2017-2021, MSc. Information and Communication Science and Engineering from Nelson Mandela African Institution of Science and Technology (NM-AIST), Tanzania 2012-2014 and Bachelors’ degree (BSc. informatics) from the Sokoine University of Agriculture (SUA), Tanzania 2008-2011.

Teaching Subjects and Research Interests

Dr Mahenge is involved in teaching undergraduate courses which include: introduction to artificial intelligence, system modelling and simulation, programming in Java, Internet programming and web server management, Database Implementation and Management, and Professional skills for IT Practitioners.

His research interest is Mobile Edge and cloud computing, recommender systems, image processing and application of artificial intelligence in Agriculture focusing on plant diseases detection, classification, and harmful pests prediction.

Research Projects

Dr. Mahenge has been involved in various research projects, some of research project include: project on optimizing the allocation and deployment of edge computing resources for complex and diverse Internet of Things (IoT) businesses, Wuhan University of Technology (WUT), China, 2017-2021(member); Enhancement of Sokoine University of Agriculture’s Capacity in Utilizing Information and Communication Technology (ESUA-CICT) project funded by USAID, SUA, Tanzania, 2012-2017(Logistic coordinator); and the Nambala & Nganana E-Reader Project implemented by NM-AIST and The Worldreader Organization, Arusha, Tanzania, 2013. Dr. Mahenge is currently a Principal Investigator (PI) of the SUA Research and Innovation Support (SUARIS) 2nd phase titled “Plant pests pRediction and Emerging Disease detection in bean leaf using Image processing and maChine learning Techniques (PREDiCT)” funded by SUA. He is also a facilitator of YEESI 105 Entrepreneurship for Artificial Intelligence in a project funded by USAID titled “Morogoro Youth Empowerment through Establishment of Social Innovation (YEESI) lab for problem-centered training in machine vision”.


Michael has co-authored several journal articles, conference proceedings, and book chapters in Mobile Computing, E-learning, M-learning and ICT4D. His publications are available on his Google Scholar profile.