Emmanuel Ukekwe | Data Analytics | Best Researcher Award Published on 29/09/202529/09/2025 by Computer Vision Awards Dr. Emmanuel Ukekwe | Data Analytics | Best Researcher Award Senior Lecturer | University of Nigeria | Nigeria Dr. Emmanuel Ukekwe is a dedicated researcher and academic with expertise in artificial intelligence, expert systems, data science, computational programming, and software engineering, with a focus on applying intelligent technologies to solve societal problems. He obtained his Bachelor of Science in Computer/Statistics, Master of Science, and Ph.D. in Computer Science from the University of Nigeria, Nsukka, where he has grown into a respected lecturer and researcher. His professional journey includes roles as Senior Lecturer, Lecturer, and Instructor, as well as administrative positions such as Acting Head of Department and Acting Dean, demonstrating both academic and leadership excellence. His research interests span the application of machine learning and Python programming in data-driven problem solving, optimization models, recommender systems, and educational technologies. He has published extensively in recognized journals and conferences indexed in Scopus, covering healthcare systems, telecommunications, student performance, and COVID-19 analytics. He has been actively involved in university committees, curriculum development, and community-based research projects, and is a member of organizations such as the National Biotechnology Development Agency and the Technical Committee on UNESCO-HP projects. His skills include statistical analysis, software development, and advanced computational modeling, reflecting strong technical and analytical capabilities. His academic and research contributions have been recognized with professional memberships and community service engagements, marking him as an influential contributor to both academia and society. His research profile records 4 citations, 8 documents, and an h-index of 1. Profiles: Google Scholar | Scopus | ORCID | ResearchGate Featured Publications Okereke, G. E., Bali, M. C., Okwueze, C. N., Ukekwe, E. C., Echezona, S. C., & Ugwu, C. I. (2023). K-means clustering of electricity consumers using time-domain features from smart meter data. Journal of Electrical Systems and Information Technology, 10(1), 2. Ukekwe, E. C., Obayi, A. A., Johnson, A., Musa, D. A., & Agbo, J. C. (2025). Optimizing data and voice service delivery for mobile phones based on clients’ demand and location using affinity propagation machine learning. Journal of the Nigerian Society of Physical Sciences, 7(2), 2109. Ukekwe, E. C., Ezeora, N. J., Obayi, A. A., Asogwa, C. N., Ezugwu, A. O., Adegoke, F. O., Raiyetumbi, J., & Tenuche, B. (2025). Examining the impact of mathematics ancillary courses on computational programming intelligence of computer science students using machine learning techniques. Computer Applications in Engineering Education, 33(4), e70054. Ukekwe, E. C., Ogbonna, G. U. G., Adegoke, F. O., Okereke, G. E., & Asogwa, C. N. (2023). Clustering Nigeria’s IDP camps for effective budgeting and re-settlement policies using an optimized K-means approach. African Conflict & Peacebuilding Review, 13(2), 60–85. Okereke, G. E., Azegba, O., Ukekwe, E. C., Echezona, S. C., & Eneh, A. (2023). An automated guide to COVID-19 and future pandemic prevention and management. Journal of Electrical Systems and Information Technology, 10(1), 16.
Dr. Emmanuel Ukekwe is a dedicated researcher and academic with expertise in artificial intelligence, expert systems, data science, computational programming, and software engineering, with a focus on applying intelligent technologies to solve societal problems. He obtained his Bachelor of Science in Computer/Statistics, Master of Science, and Ph.D. in Computer Science from the University of Nigeria, Nsukka, where he has grown into a respected lecturer and researcher. His professional journey includes roles as Senior Lecturer, Lecturer, and Instructor, as well as administrative positions such as Acting Head of Department and Acting Dean, demonstrating both academic and leadership excellence. His research interests span the application of machine learning and Python programming in data-driven problem solving, optimization models, recommender systems, and educational technologies. He has published extensively in recognized journals and conferences indexed in Scopus, covering healthcare systems, telecommunications, student performance, and COVID-19 analytics. He has been actively involved in university committees, curriculum development, and community-based research projects, and is a member of organizations such as the National Biotechnology Development Agency and the Technical Committee on UNESCO-HP projects. His skills include statistical analysis, software development, and advanced computational modeling, reflecting strong technical and analytical capabilities. His academic and research contributions have been recognized with professional memberships and community service engagements, marking him as an influential contributor to both academia and society. His research profile records 4 citations, 8 documents, and an h-index of 1. Profiles: Google Scholar | Scopus | ORCID | ResearchGate Featured Publications Okereke, G. E., Bali, M. C., Okwueze, C. N., Ukekwe, E. C., Echezona, S. C., & Ugwu, C. I. (2023). K-means clustering of electricity consumers using time-domain features from smart meter data. Journal of Electrical Systems and Information Technology, 10(1), 2. Ukekwe, E. C., Obayi, A. A., Johnson, A., Musa, D. A., & Agbo, J. C. (2025). Optimizing data and voice service delivery for mobile phones based on clients’ demand and location using affinity propagation machine learning. Journal of the Nigerian Society of Physical Sciences, 7(2), 2109. Ukekwe, E. C., Ezeora, N. J., Obayi, A. A., Asogwa, C. N., Ezugwu, A. O., Adegoke, F. O., Raiyetumbi, J., & Tenuche, B. (2025). Examining the impact of mathematics ancillary courses on computational programming intelligence of computer science students using machine learning techniques. Computer Applications in Engineering Education, 33(4), e70054. Ukekwe, E. C., Ogbonna, G. U. G., Adegoke, F. O., Okereke, G. E., & Asogwa, C. N. (2023). Clustering Nigeria’s IDP camps for effective budgeting and re-settlement policies using an optimized K-means approach. African Conflict & Peacebuilding Review, 13(2), 60–85. Okereke, G. E., Azegba, O., Ukekwe, E. C., Echezona, S. C., & Eneh, A. (2023). An automated guide to COVID-19 and future pandemic prevention and management. Journal of Electrical Systems and Information Technology, 10(1), 16.