Ph.D student candidate, Chongqing university of posts and telecommunications, China
Elhadj Moustapha Diallo is a dedicated researcher and engineer specializing in Information and Communication Engineering ๐ก. With extensive experience in telecommunications, signal processing, and network optimization, he has contributed significantly to cutting-edge advancements in energy-efficient resource allocation, UAV-enabled networks, and deep learning applications in wireless systems. His expertise spans both academia and industry, having worked with top organizations such as Transsion, Huawei, and MTN. His research has been widely recognized, leading to multiple publications in prestigious IEEE conferences and journals ๐.
Publication Profile
๐ Education
Elhadj Moustapha Diallo is currently pursuing his Ph.D. in Information and Communication Engineering at Chongqing University of Posts and Telecommunications, China (2021-2025) ๐. He previously earned a Masterโs degree in the same field (2018-2021) and holds a Bachelor’s degree in Telecommunications from the University Nongo Conakry, Guinea (2012-2021) ๐ก. His academic journey is marked by strong expertise in wireless communications, artificial intelligence applications, and optimization techniques in modern telecommunication systems.
๐ผ Experience
With a solid background in both research and industry, Diallo has served as an Image Evaluation Engineer at Transsion Company in China, where he specialized in image analysis and mobile camera evaluation ๐ท. His research work at the Chongqing Key Laboratory of Signal and Information Processing focused on 5G mobile communications, resource allocation, and IoT networks ๐. Prior to that, he gained valuable experience in IT support, network engineering, and telecommunications at MTN, Huawei Technology Training Center, and Contact Center International ๐ง.
๐ Awards and Honors
Elhadj Moustapha Diallo has been recognized for his contributions to communication engineering, particularly in energy-efficient wireless networks ๐
. His research has been accepted at high-profile IEEE conferences, and he has actively collaborated with leading experts in the field. His achievements in optimizing telecommunication systems using deep learning and UAV-assisted networks have positioned him as an emerging expert in wireless technologies ๐.
๐ฌ Research Focus
Dialloโs research interests include energy-efficient resource allocation, UAV-enabled networks, deep learning for wireless communications, and optimization techniques for 5G and beyond ๐ถ. His studies explore novel approaches such as deep unfolding mechanisms, generative models for multi-carrier NOMA networks, and long-term energy consumption minimization for UAV-assisted content fetching. His innovative contributions are shaping the future of next-generation communication systems ๐.
๐ Conclusion
Elhadj Moustapha Diallo is a highly skilled researcher and telecommunications engineer whose contributions to energy-efficient wireless networks and advanced communication technologies have earned him recognition in academia and industry ๐. His extensive research, publications, and practical experience make him a key innovator in the field of 5G, AI-driven optimization, and UAV-assisted networking. With a strong foundation in both theory and practice, Diallo continues to push the boundaries of next-generation communication systems ๐ก๐.
๐ Publications
Energy Efficient Resource Allocation and Mode Selection for Content Fetching in Cellular D2D Networks (2021) – IEEE Wireless Telecommunications Symposium (WTS) ๐ก.
Content Fetching Delay Optimization-Based Caching and Resource Allocation for UAV-Enabled Networks (2024) – IEEE Access ๐.
Optimizing Wireless Networks with Deep Unfolding: Comparative Study on Two Deep Unfolding Mechanisms (2024) – arXiv Preprint ๐ถ.
Generative Model for Joint Resource Management in Multi-Cell Multi-Carrier NOMA Networks (2024) – Accepted at IEEE 10th International Conference on Computer and Communications (ICCC 2024) ๐.
OHDRL-Based Energy Consumption Optimization for Joint Content Fetching and Trajectory Design of UAVs (2024) – Accepted at IEEE 29th Asia Pacific Conference on Communications (APCC) ๐.
Long-Term Energy Consumption-Minimization-based Joint Content Fetching and Trajectory Design of UAVs – Under review in Computer Communications ๐ฐ๏ธ.