Dr Temitayo Fagbola

Dr Temitayo Matthew Fagbola

Teaching Fellow

Faculty and Department

  • Faculty of Science and Engineering
  • Data Science AI and Modelling Centre (DAIM)

Qualifications

  • BEng
  • MSc
  • PhD / DPhil
  • PGCert (University of Hull)

Understanding Artificial Intelligence

Mathematics of Artificial Intelligence

Deep Learning

Applied AI

Natural Language Processing

Recent outputs

View more outputs

Conference Proceeding

Lexicon-Based Sentiment Analysis and Emotion Classification of Climate Change Related Tweets

Fagbola, T. M., Abayomi, A., Mutanga, M. B., & Jugoo, V. (2022). Lexicon-Based Sentiment Analysis and Emotion Classification of Climate Change Related Tweets. In Proceedings of the 13th International Conference on Soft Computing and Pattern Recognition (SoCPaR 2021) (637-646). https://doi.org/10.1007/978-3-030-96302-6_60

Journal Article

Special issue "Towards a higher education of the future: Transformational roles of edge intelligence"

Doshi, R., Hu, Y. C., Garg, L., & Fagbola, T. (2024). Special issue “Towards a higher education of the future: Transformational roles of edge intelligence”. Array, 22, Article 100332. https://doi.org/10.1016/j.array.2023.100332

An SAP Enterprise Resource Planning Implementation Using a Case study of Hospital Management System for Inclusion of Digital Transformation

Aroba, O. J., Owoputi, A. O., & Fagbola, T. M. (2023). An SAP Enterprise Resource Planning Implementation Using a Case study of Hospital Management System for Inclusion of Digital Transformation. International Journal of Computer Information Systems and Industrial Management Applications, 15(2023), 154-165

Smart Face Masks for Covid-19 Pandemic Management: A Concise Review of Emerging Architectures, Challenges and Future Research Directions

Fagbola, T. M., Fagbola, F. I., Aroba, O. J., Doshi, R., Hiran, K. K., & Thakur, S. C. (2023). Smart Face Masks for Covid-19 Pandemic Management: A Concise Review of Emerging Architectures, Challenges and Future Research Directions. IEEE sensors journal, 23(2), 877-888. https://doi.org/10.1109/JSEN.2022.3225067

In silico identification of chemical compounds in Spondias mombin targeting aldose reductase and glycogen synthase kinase 3β to abate diabetes mellitus

Ajiboye, B. O., Fagbola, T. M., Folorunso, I. M., Salami, A. W., Aletile, O. N., Akomolede, B. A., …Oyinloye, B. E. (2023). In silico identification of chemical compounds in Spondias mombin targeting aldose reductase and glycogen synthase kinase 3β to abate diabetes mellitus. Informatics in Medicine Unlocked, 36, Article 101126. https://doi.org/10.1016/j.imu.2022.101126

Research interests

* Social computing AI and NLP

* efficiency of methods and models, and data efficiency

* transfer and small-data learning

* generative deep learning, unsupervised deep learning and stochastic optimisation

* biomedical and public health applications

* fairness and ethical application of ML

Awards and prizes

Inspired in Hull Awards

2023

The ‘Excellence through Feedback’ award - WINNER The ‘Excellence in Teaching’ - RUNNER-UP

Membership/Fellowship of professional body

FHEA

2024

Fellowship of the Higher Education Academy

National/International learned society/body role

MBCS

2024

Member, British Computer Society. The Chartered Institute for IT

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