Dr. Yirga Yayeh Munaye, a dynamic Assistant Professor at Injibara University, Ethiopia 🇪🇹, stands out for his expertise in deep learning, AI, and UAV-based wireless networks 🤖📡. With a PhD and extensive publications in prestigious journals 📚, Dr. Yirga has led cutting-edge research on human activity recognition, breast cancer detection, and drone base station deployment 🌐. His roles include Director of E-learning Management and postgraduate research coordination 🧑🏫. He actively mentors MSc and PhD students, fostering the next generation of researchers 🎓. His strong programming skills in TensorFlow, Python, and C++ 🖥️, combined with his leadership in data science and cybersecurity, position him as a valuable contributor to academia and beyond. His commitment to research excellence and innovation makes him an exemplary candidate for the Best Researcher Award 🏆.
Dr. Yirga Yayeh Munaye earned his Ph.D. in Computer Science from Universiti Teknologi Malaysia, where he honed his expertise in deep learning and AI 🤖. His academic journey began with a Bachelor of Science in Information Technology from Wolaita Sodo University, Ethiopia, followed by a Master’s degree in Computer Science from Addis Ababa University 📖. Throughout his studies, Dr. Yirga demonstrated a strong commitment to academic excellence, consistently ranking among the top of his class and engaging in numerous research collaborations 🔍. His educational background laid a solid foundation for his specialization in AI-driven human activity recognition, drone base stations, and IoT systems 🌐. Dr. Yirga’s robust educational achievements make him a highly qualified and respected academic in the fields of computer science and technology 👨🎓.
Currently serving as an Assistant Professor at Injibara University, Ethiopia 🇪🇹, Dr. Yirga Yayeh Munaye has an impressive track record of leadership and teaching. He has held key administrative roles, including Director of E-Learning Management and Head of the Department of Computer Science 🎓. Dr. Yirga has spearheaded multiple research projects, integrating AI and UAV technologies into real-world solutions 📡. His mentorship extends to supervising MSc and PhD students, shaping the next generation of innovators 🧑🔬. Beyond teaching, he has contributed to academic governance, quality assurance, and curriculum development 🗂️. His extensive experience includes collaborative international research and publishing in high-impact journals, highlighting his commitment to advancing science globally 🌍. Dr. Yirga’s diverse professional experiences make him a versatile and respected academic leader 🤝.
Dr. Yirga Yayeh Munaye’s research interests span deep learning, AI-driven computer vision, and UAV-based wireless networks 🤖🚁. He has extensively explored human activity recognition, breast cancer detection using machine learning, and drone base station deployment for communication networks 📶. His passion lies in integrating AI with IoT to create intelligent systems that solve real-world problems, particularly in healthcare and agriculture 🌱❤️. Dr. Yirga is also deeply invested in cybersecurity and data science, focusing on securing wireless networks and developing robust, scalable AI models 🔒📊. His innovative work on the synergy between deep learning algorithms and practical applications positions him at the forefront of modern AI research 🌐. Dr. Yirga’s commitment to impactful research aligns perfectly with global efforts to harness AI for societal benefit 🏆.
Dr. Yirga Yayeh Munaye has received multiple awards and honors recognizing his outstanding contributions to AI, deep learning, and drone-based communication networks 🤖📡. He has been acknowledged with Best Paper Awards at international conferences and recognized for his excellence in research, innovation, and teaching 🎓. His commitment to fostering academic growth and excellence earned him accolades at the university and national levels 🏆. Notably, his research on breast cancer detection and human activity recognition has garnered significant attention, positioning him as a leading researcher in Ethiopia 🇪🇹 and beyond 🌍. Dr. Yirga’s dedication to impactful research, mentorship, and community development reflects his unwavering commitment to advancing technology for societal progress 🔬❤️
Dr. Yirga Yayeh Munaye is highly skilled in deep learning frameworks such as TensorFlow and PyTorch 🤖. He is proficient in Python, C++, and MATLAB, enabling him to develop and deploy advanced AI models effectively 💻. Dr. Yirga’s expertise includes data preprocessing, feature extraction, and model optimization, crucial for human activity recognition and medical image analysis 🏥📈. His skill set extends to cloud computing, data security, and the integration of AI with UAVs and IoT systems ☁️🚁. He is also an accomplished academic writer, publishing extensively in high-impact journals and guiding students through their research journeys ✍️🎓. Dr. Yirga’s comprehensive skill set in programming, data analysis, and AI deployment positions him as a versatile researcher driving technological advancement 📊🚀.
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Cyber security: State of the art, challenges and future directions
Authors: WS Admass, YY Munaye, AA Diro
Year: 2024
Citations: 185
Source: Cyber Security and Applications 2, 100031
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UAV positioning for throughput maximization using deep learning approaches
Authors: YY Munaye, HP Lin, AB Adege, GB Tarekegn
Year: 2019
Citations: 60
Source: Sensors 19 (12), 2775
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An indoor and outdoor positioning using a hybrid of support vector machine and deep neural network algorithms
Authors: AB Adege, HP Lin, GB Tarekegn, YY Munaye, L Yen
Year: 2018
Citations: 58
Source: Journal of Sensors 2018 (1), 1253752
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Applying Deep Neural Network (DNN) for large-scale indoor localization using feed-forward neural network (FFNN) algorithm
Authors: AB Adege, L Yen, H Lin, Y Yayeh, YR Li, SS Jeng, G Berie
Year: 2018
Citations: 38
Source: 2018 IEEE International Conference on Applied System Invention (ICASI), 814-817
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Big data: security issues, challenges and future scope
Authors: GB Tarekegn, YY Munaye
Year: 2016
Citations: 37
Source: International Journal of Computer Engineering & Technology 7 (4), 12-24
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Deep-reinforcement-learning-based drone base station deployment for wireless communication services
Authors: GB Tarekegn, RT Juang, HP Lin, YY Munaye, LC Wang, MA Bitew
Year: 2022
Citations: 33
Source: IEEE Internet of Things Journal 9 (21), 21899-21915
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Indoor localization using K-nearest neighbor and artificial neural network back propagation algorithms
Authors: AB Adege, Y Yayeh, G Berie, H Lin, L Yen, YR Li
Year: 2018
Citations: 33
Source: 2018 27th Wireless and Optical Communication Conference (WOCC), 1-2
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Convolutional neural networks and histogram-oriented gradients: a hybrid approach for automatic mango disease detection and classification
Authors: WS Admass, YY Munaye, GA Bogale
Year: 2024
Citations: 32
Source: International Journal of Information Technology 16 (2), 817-829
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Deep reinforcement learning based resource management in UAV-assisted IoT networks
Authors: YY Munaye, RT Juang, HP Lin, GB Tarekegn, DB Lin
Year: 2021
Citations: 32
Source: Applied Sciences 11 (5), 2163
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Mobility prediction in mobile ad-hoc network using deep learning
Authors: Y Yayeh, H Lin, G Berie, AB Adege, L Yen, SS Jeng
Year: 2018
Citations: 26
Source: 2018 IEEE International Conference on Applied System Invention (ICASI), 1203
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DFOPS: Deep-Learning-Based Fingerprinting Outdoor Positioning Scheme in Hybrid Networks
Authors: GB Tarekegn, RT Juang, HP Lin, AB Adege, YY Munaye
Year: 2020
Citations: 22
Source: IEEE Internet of Things Journal 8 (5), 3717-3729
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Resource allocation for multi-UAV assisted IoT networks: A deep reinforcement learning approach
Authors: YY Munaye, RT Juang, HP Lin, GB Tarekegn
Year: 2020
Citations: 13
Source: 2020 International Conference on Pervasive Artificial Intelligence (ICPAI)
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Applying long short-term memory (LSTM) mechanisms for fingerprinting outdoor positioning in hybrid networks
Authors: GB Tarekegn, HP Lin, AB Adege, YY Munaye, SS Jeng
Year: 2019
Citations: 12
Source: 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 1-5
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Integration of feature enhancement technique in Google inception network for breast cancer detection and classification
Authors: AO Admass, WS Munaye, YY Munaye, Salau
Year: 2024
Citations: 8
Source: Journal of Big Data 11 (78), https://doi.org/10.1186/s40537-024-00936
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Channel quality estimation in 3D drone base station for future wireless network
Authors: GB Tarekegn, RT Juang, HP Lin, YY Munaye, LC Wang, SS Jeng
Year: 2021
Citations: 8
Source: 2021 30th Wireless and Optical Communications Conference (WOCC), 236-239
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Radio resource allocation for 5G networks using deep reinforcement learning
Authors: YY Munaye, RT Juang, HP Lin, GB Tarekegn, DB Lin, SS Jeng
Year: 2021
Citations: 8
Source: 2021 30th Wireless and Optical Communications Conference (WOCC), 66-69
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Integrating case-based and rule-based reasoning for diagnosis and treatment of mango disease using data mining techniques
Authors: WS Admass, YY Munaye
Year: 2024
Citations: 7
Source: International Journal of Information Technology 16 (3), 1699-1715
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SRCLoc: Synthetic radio map construction method for fingerprinting outdoor localization in hybrid networks
Authors: GB Tarekegn, RT Juang, HP Lin, LC Tai, YY Munaye, MA Bitew
Year: 2022
Citations: 7
Source: IEEE Sensors Journal 22 (15), 15574-15583
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Automatic detection and classification of mango disease using convolutional neural network and histogram oriented gradients
Authors: WSema, Y Yayeh, G Andualem
Year: 2023
Citations: 6
Source: 2023
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Reduce fingerprint construction for positioning IoT devices based on generative adversarial nets
Authors: GB Tarekegn, RT Juang, HP Lin, YY Munaye, AB Adege
Year: 2020
Citations: 6
Source: 2020 International Conference on Pervasive Artificial Intelligence (ICPAI)
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Hybrid deep learning‐based throughput analysis for UAV‐assisted cellular networks
Authors: Y Yayeh Munaye, RT Juang, HP Lin, G Berie Tarekegn
Year: 2020
Citations: 6
Source: IET Communications 14 (22), 3955-3966
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Deep learning-based throughput estimation for UAV-Assisted network
Authors: YY Munaye, AB Adege, GB Tarekegn, YR Li, HP Lin, SS Jeng
Year: 2019
Citations: 6
Source: 2019 IEEE 90th Vehicular Technology Conference (VTC2019-Fall), 1-5
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Machine learning based soil-type classification
Authors: E Enawugaw, Y Yayeh
Year: 2023
Citations: 5
Source: 2023 International Conference on Information and Communication Technology
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Mobility prediction in wireless networks using deep learning algorithm
Authors: AB Adege, HP Lin, GB Tarekegn, Y Yayeh
Year: 2020
Citations: 5
Source: Advances of Science and Technology: 7th EAI International Conference, ICAST
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Application of digital cloud libraries for Ethiopian public higher learning institutions (EPHLIS)
Authors: GB Tarekegn, YY Munaye
Year: 2016
Citations: 5
Source: Int. J. Comput. Eng. Technol 7 (3), 187-197
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Gex’ez-English Bi-Directional Neural Machine Translation Using Transformer
Authors: S Getachew, Y Yayeh
Year: 2023
Citations: 3
Source: 2023 International Conference on Information and Communication Technology
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Advances of Science and Technology: 7th EAI International Conference, ICAST 2019, Bahir Dar, Ethiopia, August 2–4, 2019, Proceedings
Authors: NG Habtu, DW Ayele, SW Fanta, BT Admasu, MA Bitew
Year: 2020
Citations: 2
Source: Springer Nature
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Assessing knowledge sharing obstacles on academic staffs in Assosa University Ethiopia
Authors: YYS Ferede
Year: 2016
Citations: 2
Source: International Journal of Current Research 8 (11), 41024-41029
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Signature Recognition System Using Artificial Neural Network
Authors: YY Munaye, GB Tarekegn
Year: 2018
Citations: 1
Source: European Journal of Computer Science and Information Technology 6 (2), 42-47
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Application of rule-based reasoning system for council HIV/AIDS patients
Authors: YY Munaye, GB Tarekegn
Year: 2016
Citations: 1
Source: International Journal of Computer Engineering & Technology 7 (4), 48-58
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Hybrid Deep Learning Methods for Human Activity Recognition and Localization in Outdoor Environments
Authors: YY Munaye, M Addis, Y Belayneh, A Molla, W Admass
Year: 2025
Source: Algorithms 18 (4), 235
Dr. Yirga Yayeh Munaye embodies the spirit of innovation and dedication in academia and research 🧑🏫🔬. His exceptional educational background, diverse professional experiences, and cutting-edge research interests make him a standout scholar in AI, deep learning, and UAV technologies 🤖🚁. Dr. Yirga’s numerous awards and recognitions highlight his impactful contributions to science and society, while his extensive skills in programming and data analysis underscore his technical excellence 🖥️📊. As a mentor and leader, he inspires students and colleagues alike, fostering a culture of innovation and collaboration 🤝🎓. Dr. Yirga’s unwavering commitment to excellence and societal progress solidifies his place as an invaluable asset to the academic and research communities worldwide 🌍🏆.