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Committed to training the next generation of engineers through hands-on learning, practical problem-solving, and research-based education.
Courses offered in the 2024/2025 academic session.
Fundamentals of IoT architecture, sensor networks, communication protocols, and practical IoT application development.
Advanced concepts in embedded systems including real-time operating systems, hardware-software co-design, and low-power design techniques.
Research methodology, academic writing, and presentation skills for graduate students in computer engineering.
Theory and application of digital signal processing including filtering, spectral analysis, and real-time implementation.
I supervise graduate students working on embedded systems, IoT, and machine learning applications.
Smart Water Management Systems
Expected: 2026
Machine Learning in Cloud and Edge Computing Sec
Expected: 2028
Machine Learning for Predictive Maintenance
Computer Vision for Traffic Monitoring
Expected: 2028
Smart Water Management Systems
Smart Water Management Systems
| Name | Degree | Research Focus | Current Position |
|---|---|---|---|
| David O. Eze | PhD (2023) | Resilient Communication Protocols | Lecturer, Federal University of Technology Owerri |
| Mercy A. Obot | Masters (2022) | Solar-Powered Monitoring Systems | Research Engineer, NASENI |
I believe in a hands-on approach to engineering education that bridges theory and practice. My goal is to equip students with not just technical knowledge, but also problem-solving skills and the ability to create meaningful solutions for real-world challenges.
I emphasize project-based learning, encouraging students to work on problems relevant to our local context while maintaining global standards of excellence. This approach has proven effective in preparing graduates who are both technically competent and socially aware.