Heads of Department and Lecturers
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Dr. Patrick Kudjo leads the School of Computing and Technology at Wisconsin International University College, overseeing academic direction, faculty, and departmental strategy across all computing programmes.
- WCB303 — Operating System Security
Research interests to be added.
Publications to be added.
Educational background to be added.
Charles Jnr. Asiedu, widely known as Babbage, is a seasoned educator and researcher with a distinguished background in Information Technology and Artificial Intelligence. He earned his Bachelor of Science in Information Technology from Wisconsin International University College, graduating as the Valedictorian of his class. He subsequently completed his national service at the University of Ghana Business School, contributing to the Operations and Management Information Systems Department. Charles holds a research-based Master's degree in Engineering from Huzhou University, China, awarded through a competitive merit-based Chinese scholarship for academic excellence. His specialization in Intelligent Information Processing Technology advanced his work in artificial intelligence, culminating in his research thesis titled "Sentiment Analysis on Twitter Data: A Performance Gap Between Deep Learning and Traditional Machine Learning Algorithms." Throughout his career, he has contributed to curriculum development for CTVET institutions, consulted for various organizations, and published research in respected journals. His research interests focus on Artificial Intelligence, Machine Learning applications, and their intersection with Healthcare and Education.
- WIT105 — Fundamentals of ICT
- WIT102 — Programming with Python
- WIT214 — Programming in Java
- ITW304 — Wireless and Mobile Computing
- ITW416 — Data Mining
- ITW422 — Advanced Mobile Application Development
Artificial Intelligence, Machine Learning applications, and their intersection with Healthcare and Education.
- Research thesis: "Sentiment Analysis on Twitter Data: A Performance Gap Between Deep Learning and Traditional Machine Learning Algorithms" — Huzhou University
- Additional research published in peer-reviewed journals (full list to be added)
- Master's in Engineering (research-based), Huzhou University, China — merit-based Chinese scholarship; specialisation in Intelligent Information Processing Technology
- National Service, University of Ghana Business School — Operations and Management Information Systems Department
- Bachelor of Science in Information Technology, Wisconsin International University College — graduated Valedictorian
Dr. Richard Amankwah is the Head of the Information Technology Department at the School of Computing and Technology, where he oversees the BSc Information Technology and Diploma in Information Technology programmes, curriculum development, and student research supervision. He holds a PhD in Computer Application Technology from Jiangsu University, China, where his doctoral research focused on software vulnerability detection and severity prediction. He earned an MSc in Information Technology from Sikkim Manipal University, India, and a BEd in Information Technology from the University of Education, Winneba. Dr. Amankwah brings more than two decades of teaching experience across Ghanaian universities and colleges of education, spanning undergraduate and postgraduate computer science and information technology, and has supervised numerous undergraduate and graduate research projects. He has served for many years as a Chief Examiner with the West African Examinations Council (WAEC) and has contributed to test-item development for the National Teaching Council's Ghana Teacher Licensure Examination. His research centres on software security — vulnerability detection methods and tools, the severity assessment of vulnerabilities reported by open-source and commercial web scanners, and the use of Bellwether analysis to predict vulnerable software components. His work has appeared in peer-reviewed journals and been presented at international venues including the IEEE International Conference on Trust, Security and Privacy in Computing and Communications and the ECOOP/ISSTA Doctoral Symposium. His broader professional background spans IT infrastructure, consultancy, data science, and cyber-security management, and he is a recipient of the T-TEL Challenge Fund award.
- ITW205 — Website Programming
- ITW322 — Advanced Website Programming
- ITW407 — Information Systems Security Management
Software vulnerability detection and severity prediction, web application security, software defect prediction using Bellwether analysis, and machine-learning approaches for secure and reliable software systems.
- Amankwah, R., Chen, J., Kudjo, P. K., & Towey, D. (2020). An empirical comparison of commercial and open-source web vulnerability scanners.
- Amankwah, R., Chen, J., Kudjo, P. K., Agyemang, B. K., & Amponsah, A. A. (2020). An automated framework for evaluating open-source web scanner vulnerability severity.
- Amankwah, R., Chen, J., Mensah, S., & Kudjo, P. K. (2020). The effect of Bellwether analysis on software vulnerability severity prediction models.
- Amankwah, R., Chen, J., Amponsah, A. A., Ocran, V., & Anang, C. O. (2020). Fast bug detection algorithm for identifying potential vulnerabilities in Juliet test cases.
- Amankwah, R., Agyeman, B. K., Mensah, K., Brew, B., & Antwi, S. Y. (2018). An integrated approach for detecting security vulnerabilities in web applications: a theoretical perspective.
- Amankwah, R., Chen, J., & Mensah, S. (2018). Predicting vulnerable software components via Bellwethers.
- Amankwah, R., & Antwi, S. Y. (2017). Evaluation of software vulnerability detection methods and tools: a review.
- Ben-Bright, B., Zhan, Y., Ghansah, B., Amankwah, R., et al. (2017). Taxonomy and a theoretical model for feedforward neural networks.
- Adjardjah, W., Amankwah, R., Okine, A. A., et al. (2017). A fuzzy logic QoE enhancement VHO scheme for VLC-RF HetNet in an indoor environment.
- PhD Computer Application Technology, Jiangsu University, China
- MSc Information Technology, Sikkim Manipal University, India
- BEd Information Technology, University of Education, Winneba
Dr. Leonard Kyei heads the Mathematics Applications unit at the School of Computing and Technology, teaching statistics and quantitative methods across several programmes.
- ITW202 — Probability and Statistics
- WBS308 — Research Methods
- WCA104 — Probability Theory and Distribution
- WCA412 — Statistical Inference
- WMT106 — Basic Statistics
Research interests to be added.
Publications to be added.
Educational background to be added.
Mr. Edwin Agbah serves as Head of the IT Support Department and oversees institutional networking and server infrastructure management. With extensive Cisco-based networking training, he manages routing, switching, infrastructure security, and enterprise system reliability across campus environments. He bridges academic instruction with enterprise-grade systems administration, ensuring high availability and operational continuity.
- ITW312 — Systems Administration
- ITW316 — Data Communication & Networks II
- WCB207 — Intro to Penetration Testing
- WCB301 — Web Application Security
Research interests to be added.
Publications to be added.
Educational background to be added.
Dr. Ian Asare is a results-driven, versatile Business and Information Systems professional with 10+ years of experience acquired through working in some national and multinational organisations.
- ITW204 — Intro to Software Engineering
Cloud infrastructure design, scalable systems, and the deployment models used by modern enterprise platforms.
Publications to be added.
Educational background to be added.
Dr. Mateko Okantey is a lecturer at the School of Computing and Technology, specialising in systems analysis, e-commerce, and e-business. She guides students through the full systems development lifecycle, from requirements gathering and analysis to designing e-business solutions that meet real organisational needs.
- WIT301 — Management Information Systems
How organisations design, analyse, and implement information systems that support online commerce and digital business operations.
Publications to be added.
Educational background to be added.
Emmanuel Junior Tapany is a Lecturer, Computer Scientist, researcher, academic mentor, and emerging scholar in Artificial Intelligence and advanced computing. He currently serves as the Postgraduate Coordinator for the School of Computing and Technology (SCOT), where he represents the Graduate School within SCOT; with dexterity He leads the coordination of postgraduate academic activities, communication, student progression, and related graduate-school functions under the auspices of the Dean of SCOT. He is currently pursuing a PhD in Computer Science and holds both an MPhil in Computer Science and a BSc in Computer Science. His research interests span Artificial Intelligence, Machine Learning, Deep Learning, Graph Neural Networks (GNNs), Capsule Neural Networks (CapsNets), Computer Vision, Edge AI and Edge Deployment, Data Science and Analytics, and intelligent applications in biometrics, health and agriculture. His doctoral research trajectory is increasingly incorporating Graph Neural Networks and graph-based representation learning, while building on his previous research experience in Capsule Neural Networks, artificial neural networks, biometric signature verification and intelligent computer vision systems. His previous research includes a Capsule Neural Network approach for bilingual writer-independent offline signature identification and verification, while his doctoral work explores scalable neural architectures, robustness benchmarking and edge deployment. As an academic, Emmanuel combines teaching, research and practical computing education. He currently teaches at Wisconsin International University College, Ghana with teaching experience covering Artificial Intelligence, Principles of Programming, Networking Fundamentals, IT Service Management, Multimedia Applications, Computer Hardware and Software, Introduction to AI (tailored for Robotics) and Distributed Systems. He has also supervised undergraduate research projects in areas including AI-powered crop disease detection, digital agriculture, blockchain-based identity management and mobile application development. Beyond teaching and research, Emmanuel brings over two decades of active leadership orientation and service, having developed his leadership journey from student and community leadership into academic administration, coaching, counselling and mentorship. He has served in roles including Head Boy, House Captain, University Association President, Planning Committee Chairman and Secretary, Academic Coach. His leadership philosophy is centered on service, personal development, responsibility, growth and creating opportunities for others to succeed. A defining part of his professional identity is his passion for mentoring, developing and inspiring young minds towards excellence and greatness. He views education not merely as the transfer of technical knowledge, but as an opportunity to identify potential, cultivate confidence, encourage innovation and help students develop the character, competence and resilience required to become successful professionals, researchers and leaders. His broader professional interests extend into responsible AI, secure data analytics, quantum computing, blockchain technologies and emerging computing paradigms. He participated in the QWorld QIntern 2023 programme, where his team worked on securing electoral processes using classical and quantum blockchain technology and received a 3rd Best Team Award. He has also contributed to peer-reviewed research publications in areas including MANET security and hybrid metaheuristic optimization. Ultimately, Emmanuel's academic and professional vision is to contribute to the development of efficient, trustworthy and intelligent computing systems, while using research, teaching, leadership and mentorship to inspire the next generation of African scientists, technologists, innovators and leaders to realise their full potential and make meaningful contributions to society.
- ITW208 — IT Service Management
- ITW308 — Distributed Systems
- ITW403 — Artificial Intelligence
- WCB104 — Networking Fundamentals
- WIAR123 — Introduction to Artificial Intelligence
- WIT211 — Principles of Programming
Artificial Intelligence and Machine Learning, with particular interests in Deep Learning, Graph Neural Networks, Computer Vision, Capsule Neural Networks, Explainable AI, Trustworthy AI, Data Science, and efficient learning architectures for real-world and resource-constrained environments.
- Agor, A. D., Kwesi Oberko, P. S., Dotse, S. K., Partey, B. T., Aboagye-Darko, D., & Tapany, E. J. (2026). A descriptive systematic review of contemporary MANET security research: themes, design structures, and reporting rigor. Future Technology, 5(2), 69–80.
- Agor, A. D., Banaseka, F. K., Oberko, P. S. K., Banning, L. A., Dotse, S. K., & Tapany, E. J. (2026). A systematic review of metaheuristic–metaheuristic (MH–MH) hybridizations for optimization. Journal of Computer Science, 22(2), 660–678. DOI: 10.3844/jcssp.2026.660.678.
- PhD Computer Science, Ghana Communication Technology University (Ongoing)
- MPhil Computer Science, University of Energy & Natural Resources
- BSc Computer Science, University of Energy & Natural Resources
Biography coming soon.
- DIT208 — Computer Graphics
- ITW405 — E-Business and E-Commerce
- ITW413 — Project Management
- WCA105 — Computer Systems
- WCB101 — Introduction to Cybersecurity
- WIT105 — Information Technology Fundamentals
Research interests to be added.
Publications to be added.
Educational background to be added.
Biography coming soon.
- ITW301 — Web Technologies
- ITW325 — Information Systems Research Methods
Research interests to be added.
Publications to be added.
Educational background to be added.
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Madam Edith
Faculty Officer
