Personal profile

Academic Biography

Olugbenga is a professor in digital innovation at Teesside University with a passion for developing intelligent solutions for low-carbon economy. Olugbenga holds a PhD in AI-driven Building Information Modelling (BIM) for low-waste construction from the University of the West of England (UWE) Bristol. He worked at UWE Bristol as an Associate Professor with a focus on immersive technologies and AI development for industrial applications prior to joining Teesside University. His research interests include business applications of immersive technologies, digital twin for engineering processes, and the application of emerging technologies for climate adaptation and resilience. He has worked with large businesses and SMEs on research grants (funded by Innovate UK, EPSRC and BEIS) with a total project value of £18.7 million. The focus of the projects include computer vision for onsite processes and safety, BIM for carbon minimisation, conversational-AI for boosting construction productivity, augmented reality for infrastructure maintenance, and digital twin for airplane dynamics simulation.

Summary of Research Interests

•    Intelligent systems for low-carbon economy
•    Industrial applications of immersive technologies
•    Digital twin for engineering processes
•    Emerging technologies for climate adaptation and resilience

Research Projects & External Funding

  • Computer Vision and IoT for Personalised Site Monitoring Analytics in Real-Time towards Behaviour-Based Safety (CV-SMART). Funded by Innovate UK @ £799,999.
  • IntelliSite: enabling safer and more efficient construction through video analytics and machine learning. UKRI Ideas to Address COVID-19@£832,243.
  • AI System for Predicting Embodied Carbon (ASPEC) in Infrastructure Projects”. Funded by Innovate UK @ £800,000.
  • Transport Infrastructure Efficiency Strategy (TIES) Living Lab. Funded by Innovate UK@£16.278 million.

Learning and Teaching Interests and Activities

I am teaching the following modules in the 2022/23 academic year:

  • Semester 1: Ethics for AI
  • Semester 2: Artificial Intelligence Ethics and Applications



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Collaborations and top research areas from the last five years

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