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Bio
Dr. Otebolaku is a Senior Lecturer (Assistant Professor) in Computing at Sheffield Hallam University (SHU), where he contributes to both undergraduate (Software Engineering, Computer Science and Artificial Intelligence) and postgraduate (Big Data Analytics) programs. His academic journey includes studying Computer Engineering in Nigeria and Computer Science in South Africa, culminating in a PhD in Electrical and Computer Engineering (Telecommunication Engineering) from the University of Porto, Portugal.
Before joining SHU, Dr. Otebolaku gained experience as a Systems Engineer in the ICT industry and held Postdoctoral Research Associate positions at Liverpool John Moores University (UK) and the University of Aveiro (Portugal), where he was also affiliated with the Institute of Telecommunications. From 2009 to 2015, he was a Research and Development Engineer at INESC TEC in Portugal.
An active researcher, Dr. Otebolaku has participated in numerous projects, including European H2020 initiatives. His research interests broadly encompass mobile/pervasive computing and ambient intelligence, with a specific focus on context awareness, activity context recognition, mobile data management, and IoT-driven personalised services. He has been awarded various scholarships and grants, including INESC TEC doctoral research grants, a full doctoral grant from Portugal's Fundacao para Ciencia e a Tecnologia (FCT), and a Master's grant from the University of Zululand. He is also a recipient of Microsoft travel grants.
Research
His research leverages Artificial Intelligence (AI) and Machine Learning (ML) within context sensing systems to solve real-world problems. His core interests lie in ambient intelligence, context-awareness, and mobile data management.
Specifically, his work has focused on improving mobile multimedia systems through intelligent delivery and consumption, using insights gleaned from smartphone sensory data. He also has a keen interest in "Trustworthy Edge Intelligence".
Furthermore, he has tackled challenges in human activity context recognition and its application in building personalized user preferences, often involving the deployment of intelligent applications on smart devices.
Currently, his research applies AI/Machine Learning, Edge Computing, and Software Engineering to address critical issues in the energy, healthcare, and environmental sectors.
Special Issues|(SI):
2. IoT, Edge Computing and AI: Enabling Emerging Intelligent Applications, MDPI Electronics
3. SDN-Enabled Sensing in Smart Infrastructure, MDPI Sensors
Conference Technical Committee
10th International Conference on Frontiers of Signal Processing (ICFSP 2025 ), Paris, France. Track Chair: Intelligent Image Processing and Multimedia Technology
10th International Conference on Frontiers of Signal Processing, Paris, France, 2025.
The 5th Asian Symposium on Signal Processing, 2024, Singapore.
9th International Conference on Frontiers of Signal Processing (ICFSP 2024 ), Paris, France.
Technical Programme Committee, 9th International Conference on Information and Communication Technologies for Ageing Well and e-Health (ICT4AWE 2023)
5th International Workshop on Pervasive and Context-Aware Middleware (PerCAM 17), Rome, Italy.
Technical Reviewer for IEEE Sensors Conference (2019)
Technical Committee member, 6th International Conference on Signal Processing (ICFSP 2021), Paris.
Technical Programme Committee member of the ICFSP (Frontier for signal processing) conference, Paris 2021
Technical Programme Committee 2021 IEEE 94th Vehicular Technology Conference.
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