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Dr Taiwo Ayodele
PhD, PBSC, MIET, FHEA

Course Leader

School of Technology and Maritime Industries

taiwo.ayodele@solent.ac.uk
Room no. JM506
Headshot - Dr Taiwo Ayodele

Biography

With over 18 years of teaching and research experience in computing and artificial intelligence, Taiwo has established himself as a dedicated scholar and educator.

His expertise spans a broad array of subjects, including computing, artificial intelligence (AI), machine learning (ML), data science, natural language processing (NLP), human-computer interaction (HCI), AI in health, information Management, information security and privacy, knowledge management, email management, computer network management and design, cloud computing, cybersecurity, databases, database management and design, the Internet of Things (IoT), software engineering, and sustainable future and technology.

Taiwo earned his PhD in Artificial Intelligence from the University of Portsmouth. Throughout his academic career, he has taught both undergraduate and postgraduate students, sharing his extensive knowledge and passion for these fields. In addition to his academic role, he has collaborated with several high-tech companies across the world, gaining substantial hands-on experience in the IT industry.

Taiwo is an active member of several prestigious professional organisations. He is a Fellow of the British Computer Society (BCS), and a Member of the Institute of Engineering and Technology (IET).

As an examiner and guest speaker at various universities across the UK, Taiwo shares his insights on topics critical to his research and consultancy work. He also contributes to the academic community as a reviewer for internationally recognised journals, including the International Journal of Advanced Computer Science and Applications (IJACSA), and the International Journal of Intelligent Computing Research (IJICR).

Taiwo has published several papers in leading academic journals and conferences, further demonstrating his commitment to advancing knowledge in his field. Notably, his work on artificial intelligence applications in machine learning has been widely cited and recognised for its contribution to the field. His research interests include artificial intelligence (AI), machine learning (ML), data science, natural language processing (NLP), human-computer interaction (HCI), cybersecurity, knowledge management, information intelligence, sustainable future and technology (with a focus on smart cities, green homes, renewable energy, and sustainable transport), and the application of AI in healthcare.

His contributions have been instrumental in driving innovation and excellence in computing and artificial intelligence.

Pure profile

View Taiwo's profile on Pure

Further information

  1. Ayodele, T.O. (2024). Enhancing Email Urgency Reply Prediction with ATAN-Transformer Fusion. In: Arai, K. (eds) Intelligent Computing. SAI 2024. Lecture Notes in Networks and Systems, vol 1016. Springer, Cham. https://doi.org/10.1007/978-3-031-62281-6_10
  2. Ayodele, T & Zhou, S 2024, Cultivating knowledge sharing in universities: An innovative approach integrating deep learning for collaborative learning platforms. in Lecture Notes in Networks and Systems.Springer Nature, Intelligent Systems Conference 2024 (IntelliSys 2024), Amsterdam, Netherlands
  3. Ayodele, T. (2020) The Future of Electric Vehicles Battery Technology. Amazon. London, UK. July 4th, 2020. pp 1-71.
  4. Ayodele, T. (2019) The Future of Electric Vehicles: A Sustainable Solution. Amazon. London, UK. September 2019. pp 1 -159.
  5. Ayodele, T., Adeegbe, D. (2014) Significance of Secure Email Communications For E-Health Services. International Journal of Advanced Computer Science and Applications (IJACSA 2014). 5 (9).
  6. Ayodele, T., Adeegbe, D. (2013) Cloud based emails boundaries and vulnerabilities. Science and Information Conference (SAI 2013). London. October 7-9. IEEE. 912-914.
  7. Ayodele, T, Akmayeva, G, Shoniregun, C.A. (2012). Machine Learning Approach Towards Email Management. World Congress on Internet Security (WorldCIS 2012), University of Guelph, Canada. June 10-12. IEEE. pp.106-109
  8. Ayodele, T, Shoniregun, C.A, Akmayeva, G. (2012). Anti-phishing Prevention Measure for Email Systems. World Congress on Internet Security (WorldCIS 2012). University of Guelph, Canada. June 10-12. IEEE pp.208-211
  9. Ayodele, T, Shoniregun, C.A, Akmayeva, G. (2011). Towards e-learning Security: A Machine Learning Approach. International Conference on Information Society (i-Society 2011). London, UK. June 27-29. IEEE. pp.490-492, 27-29
  10. Ayodele, T, Shoniregun, C.A, Zhou, S. (2011). Email Urgency Reply Prediction. International Conference on Information Society (i-Society 2011). London, UK. June 27-29. IEEE. pp.418-422
  11. Ayodele, T, Shoniregun, C.A, Akmayeva, G.A. (2011). Security Review of Email Summarization Systems. World Congress on Internet Security (WorldCIS 2011). London, UK. Feb. 21-23. pp.269-271.
  12. Ayodele, T, Zhou, S, Khusainov, R. (2010). Machine Learning Email Prediction System (MLEPS). International Journal for Infonomics (IJI). 3(4). P.345-349.
  13. Ayodele, T. (2010). Unsupervised Email Vector Space Model (UEVSM). International conference for internet technology and secured transactions (ICITST 2010), London, UK. November 8-11, 2010. IEEE, pp. 1-5.
  14. Ayodele, T, Zhou, S, Khusainov, R. (2009). Intelligent Email Prediction System (IEPS). International Conference for Internet Technology and Secured Transactions (ICITST 2009). London, UK. November 9-12. IEEE. 1-5.
  15. Ayodele, T, Zhou, S, Khusainov, R. (2010). Intelligent Email Summarisation System (IESS). International Conference on Information Society (i-Society 2010). London, UK. June 28-30. IEEE.
  16. Ayodele, T, Zhou, S, Khusainov, R. (2009). Email classification: Solution with back propagation technique. International Conference for Internet Technology and Secured Transactions (ICITST 2009). London, UK. IEEE. November 9 - 12. pp.1-6.
  17. Ayodele, T. (2009). Evolving email clustering method for email grouping: A machine learning approach. International Conference on Applications of Digital Information and Web Technologies (ICADIWT 2009). London, UK. IEEE. August 4-6. pp.357-362.
  18. Ayodele, T., Zhou, S., Khusainov, R. (20090. Applying Machine Learning Techniques for Email Reply Prediction. World Congress on Engineering (WCE 2009). Imperial College, London: International Association of Engineers (IAENG). July 1 – 3.
  19. Ayodele, T., Zhou, S., and Khusainov, R. (2009). Email Reply Prediction: A Machine Learning Approach. Human Interface 2009 on Human Interface and the Management of Information. Information and Interaction. Book Part II: Lecture Notes in Computer Science, vol. 5618. San Diego, CA. Springer-Verlag, Berlin, Heidelberg. July 19-24.114-123.
  20. T Ayodele, S Zhou, R Khusainov, (2009). Email Grouping and Summarization: An Unsupervised Learning Technique. World Congress on Computer Science and Information Engineering (CSIE 2009). Los Angeles, California, USA. IEEE Computer Society. March 31 - 2 April. pp. 575-579.
  21. Ayodele, T., Zhou, S. (2009). Applying machine learning techniques for e-mail management: Solution with intelligent e-mail reply prediction. Journal of Engineering and Technology Research (JETR 02009). 1(7). 143-151
  22. Ayodele, T., Zhou, S. (2008). Email reply prediction: Unsupervised learning approach. Third IEEE International Conference on Digital Information Management (ICDIM 2008), London, UK. IEEE. November 13 – 16. pp. 844-849.
  23. Ayodele, T., Zhou, S. (2008). Applying Machine Learning Algorithms for Email Management. Third IEEE International Conference on Pervasive Computing and Applications (ICPCA 2008). Alexandria, Egypt. IEEE. October 6 – 8. pp. 339-344.
  24. Ayodele, T., Khoussainov, R., Ndzi, D. (2007). Email Classification and Summarization: A Machine Learning Approach. IET Communications Conference on Wireless, Mobile and Sensor Networks (CCWMSN'2007). Shanghai. IET Press. pp. 805-808. ISBN 978-0-863-41836-5.

Book chapters

Ayodele, T., Zhang, Y. New Advances in Machine Learning. Intechopen. 2010.

Courses

BSc (Hons) Software Engineering

Learn how to design, develop, and maintain software applications to create innovative technology solutions and enhance user experiences on this BCS-accredited degree.

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BSc (Hons) Computer Science

Find your specialism on this BCS-accredited degree. Gain problem-solving skills, create innovative technologies, build intelligent systems, and prepare for a career leading in AI-enabled industries.

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BSc (Hons) Applied Artificial Intelligence

Gets hands-on with machine learning, data science and generative AI, learning to build real-world solutions working with industry tools, and preparing to graduate job-ready for your AI career.

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