Prof. Godfrey A. Mills is a Professor in the Computer Engineering Department at the University of Ghana. He joined the University in March 2006, bringing extensive industry experience from his time as an Electrical Engineer at the Electricity Company of Ghana (ECG).
He is a Professional Engineer and a member of the Ghana Institution of Engineering (GhIE), as well as a member of the IEEE Computer Society. Prof. Mills is also ranked among Ghana’s top scientists on the AD Scientific Index, reflecting his strong research output and academic contributions.
His research spans signal processing, embedded systems, machine learning, and cybersecurity, with applications in intelligent systems, healthcare technologies, and network security.
- BSc. Electrical and Electronic Engineering, Kwame Nkrumah University of Science and Technology (KNUST), Ghana
- MSc. Electronics and Computing Engineering, Gunma University, Japan
- PhD Electronics and Computing Engineering, Gunma University, Japan
Prof. Mills’ research focuses on the development of intelligent and secure engineering systems. His key research areas include:
- Analog and digital signal processing systems and applications
- Embedded systems for automation and control
- Machine learning model development for diverse applications
- Cryptographic techniques for data security and protection
- Mills, G. A., & Yamaguchi, I. (2005). Effects of quantization in phase-shifting digital holography. Applied Optics, 44(7), 1216–1225.
- Yamaguchi, I., Yamamoto, K., Mills, G. A., & Yokota, M. (2006). Image reconstruction only by phase data in phase-shifting digital holography. Applied Optics, 45(5), 975–983.
- Sowah, R. A., Ampadu, K. O., Ofoli, A., Koumadi, K., Mills, G. A., & Nortey, J. (2016). Design and implementation of a fire detection and control system for automobiles using fuzzy logic. IEEE Industry Applications Society Annual Meeting.
- Sowah, R. A., Ofori-Amanfo, K. B., Mills, G. A., & Koumadi, K. M. (2019). Detection and prevention of man-in-the-middle spoofing attacks in MANETs using predictive techniques in artificial neural networks. Journal of Computer Networks and Communications.
- Sefa-Yeboah, S. M., Osei Annor, K., Koomson, V. J., Saalia, F. K., Steiner-Asiedu, M., & Mills, G. A. (2021). Development of a mobile application platform for self-management of obesity using artificial intelligence techniques. International Journal of Telemedicine and Applications.
- Sowah, R. A., Kuditchar, B., Mills, G. A., Acakpovi, A., Twum, R. A., Buah, G., & Agboyi, R. (2021). HCBST: An efficient hybrid sampling technique for class imbalance problems. ACM Transactions on Knowledge Discovery from Data (TKDD), 16(3), 1–37.
- Mills, G. A., Acquah, D. K., & Sowah, R. A. (2024). Network intrusion detection and prevention system using hybrid machine learning with supervised ensemble stacking model. Journal of Computer Networks and Communications.