Solomon Ebenuwa

Dr Solomon Ebenuwa BSc, MSc

Senior Lecturer

Dr Solomon Ebenuwa holds a doctorate degree from the University of East London, PGCHE and fellow of Higher Educational Academy. His teaching experience of over three decades spans across the areas of software engineering, relational and non-relational databases, information systems, knowledge-based systems, machine learning at both undergraduate and postgraduate levels. He is an active researcher with interest in Big data, machine learning, algorithm development and optimisation in activity recognition. His research interest also includes imbalanced data and application of the context in ubiquitous systems.

Computer science

Responsibilities within the university

Lecturer in Data Science, Data Analysis, Database and other UG and PG computing modules.

Recognition
  • Fellow Higher Education Academy (FHEA).
  • Professional membership British Computer Society

Research / Scholarly interests

Databases, Data Science, Data Analytics, Data Mining, Machine learning, Big data and Activity Recognition.

Recent publications
Publications
  • Ebenuwa, Solomon H., Mhd Saeed Sharif, Mamoun Alazab, and Ameer Al-Nemrat. "Variance ranking attributes selection techniques for binary classification problem in imbalance data." IEEE Access 7 (2019): 24649-24666
  • Ebenuwa, Solomon H., Mhd Saeed Sharif, Ameer Al-Nemrat, Ali H. Al-Bayatti, Nasser Alalwan, Ahmed Ibrahim Alzahrani, and Osama Alfarraj. "Variance Ranking for Multi-Classed Imbalanced Datasets: A Case Study of One-Versus-All." Symmetry 11, no. 12 (2019): 1504
  • Nwajana, A.O., Otuka, R.I., Ebenuwa, S.H., Ihianle, I.K., Aneke, S.O. and Edoh, A.A., (2020), June. Symmetric 3dB Filtering Power Divider with Equal Output Power Ratio for Communication Systems. In 2020 International Conference on Electrical, Communication, and Computer Engineering (ICECCE) (pp. 1-4). IEEE
  • Ihianle, I.K., Nwajana, A.O., Ebenuwa, S.H., Otuka, R.I., Owa, K. and Orisatoki, M.O., (2020). A Deep Learning Approach for Human Activities Recognition from Multimodal Sensing Devices. IEEE Access
Book Section

Ihianle, I. K., Islam, S., Naeem, U., Ebenuwa, S.H. (2021). “Exploiting Patterns of Object Use for Human Activity Recognition: Exploiting Patterns of Object Use for Human Activity Recognition”, in 5G Networks and Advancements in Computing, Electronics, and Electrical Engineering, IGI-Global