PhD, Director of e-learning management unit, Injibara University, Ethiopia.
Dr. Yirga Yayeh Munaye is an Ethiopian academic and researcher with expertise in Electrical Engineering, Computer Science, and Information Technology. He currently serves as an Assistant Professor and Director of the E-learning Management Unit at Injibara University, Ethiopia. With a Ph.D. from National Taipei University of Technology, Taiwan, Dr. Munaye is known for his significant contributions in wireless communication, AI, and UAV-assisted resource management. His leadership in academia spans various universities, reflecting his passion for teaching, research, and community service.
Publication Profile
Google Scholar
🎓 Education Background
Dr. Munaye earned his Ph.D. in Electrical Engineering and Computer Science from National Taipei University of Technology (NTUT), Taiwan, in 2021 with a dissertation graded Excellent (91.4/100). Prior to that, he obtained an M.Sc. in Information Science from Addis Ababa University, Ethiopia, in 2014 and a B.Sc. in Information Technology from Bahir Dar University in 2009. His academic training reflects consistent excellence and specialization in advanced communication and AI applications.
👨🏫 Professional Experience
Dr. Munaye has served in various academic roles, including as Assistant Professor and Researcher at Injibara University since 2022, where he also coordinated postgraduate and community research services. Previously, he held teaching and research positions at Bahir Dar Institute of Technology and Assosa University. He has mentored Master’s and Ph.D. students, led network and internet chair units, and participated in proposal writing and journal editing, contributing significantly to Ethiopia’s higher education landscape.
🏆 Awards and Honors
Dr. Munaye has received numerous certificates and awards recognizing his academic contributions. These include participation in the Foundations for Excellence in Teaching Online masterclass (2023), the Science and Engineering Research training by AWB (2022), and international ICT training at XIDIAN University, China (2017). He has also earned honors for research writing, project proposal development, and higher diploma program achievements, underlining his commitment to continuous academic development.
🔬 Research Focus
Dr. Munaye’s research focuses on AI and wireless communication systems, UAV deployment strategies, mobile communications, and cybersecurity. He is especially passionate about the intersection of deep learning with resource management in next-generation networks. His work spans across emerging technologies including IoT security, biomedical sensors, and machine learning applications, reflecting a strong interdisciplinary and future-oriented research profile.
✅ Conclusion
With a career rooted in excellence, leadership, and innovation, Dr. Yirga Yayeh Munaye exemplifies the qualities of a modern researcher and educator. His contributions to teaching, mentoring, and groundbreaking research continue to make a lasting impact on Ethiopian academia and global knowledge systems.
📚 Top Publications Notes
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Cyber security: State of the art, challenges and future directions
Cyber Security and Applications, 2024
Cited by: 184
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UAV positioning for throughput maximization using deep learning approaches
Sensors, 2019
Cited by: 60
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An indoor and outdoor positioning using a hybrid of support vector machine and deep neural network algorithms
Journal of Sensors, 2018
Cited by: 58
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Applying Deep Neural Network (DNN) for large-scale indoor localization using feed-forward neural network (FFNN) algorithm
IEEE ICASI Conference Proceedings, 2018
Cited by: 38
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Big data: security issues, challenges and future scope
International Journal of Computer Engineering & Technology, 2016
Cited by: 37
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Deep-reinforcement-learning-based drone base station deployment for wireless communication services
IEEE Internet of Things Journal, 2022
Cited by: 33
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Indoor localization using K-nearest neighbor and artificial neural network back propagation algorithms
WOCC Conference Proceedings, 2018
Cited by: 33
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Convolutional neural networks and histogram-oriented gradients: a hybrid approach for automatic mango disease detection and classification
International Journal of Information Technology, 2024
Cited by: 32