Dr. Matthew Teow is a lecturer in the School of Engineering and Technology at PSB Academy. He graduated with a Bachelor of Science in Electronic and Electrical Engineering from Robert Gordon University, UK, a Master of Engineering in Electrical Engineering from Universiti Teknologi Malaysia, Malaysia, and a Doctor of Philosophy in Engineering from Multimedia University, Malaysia. He was educationally trained to specialize in computer technology. His Master's research was in artificial intelligence, and his doctoral dissertation was in data compression.

Matthew has had a diverse academic career that spans teaching at both undergraduate and postgraduate levels, holding administrative positions, serving on accreditation and quality assessment panels, and supervising research. His recent research contributes to the scientific foundations of artificial intelligence, focusing on representation theory, generative learning, and visual inference.

Educational Qualifications

• Doctor of Philosophy, Multimedia University, Malaysia, 2011.
• Master of Engineering, Universiti Teknologi Malaysia, Malaysia, 1999.
• Bachelor of Science, Robert Gordon University, UK, 1994.

Professional Registration and Memberships

• Chartered Engineer, Engineering Council, UK.
• Professional Engineer with Practising Certificate, Board of Engineers, Malaysia.
• Senior Member, Institution of Electrical and Electronics Engineers, US.
• Member, Institution of Engineering and Technology, UK.
• Member, Institution of Engineers, Malaysia.

Professional Experiences

• Lecturer, PSB Academy, Singapore, Aug 2023 - Now.
• Associate Professor, Sunway University, Malaysia, Jan 2023 - Aug 2023.
• Senior Lecturer, Sunway University, Malaysia, Aug 2019 - Dec 2022.

Publications (Selected)

• Puah, Y. T., Yew, K. H., Hassan, M. F., and Teow, M. Y. W., mbeddingROUGE: Malay News Headline Similarity Evaluation, In Proceedings of 2022 International Conference on Digital Transformation and Intelligence, pp. 01-06, 2022.
• Teow, M. Y. W., Convolutional Autoencoder for Image Denoising: A Compositional Subspace Representation Perspective. In Proceedings of 2021 IEEE 3rd International Conference on Artificial Intelligence in Engineering and Technology, pp. 1-6, 2021.
• Puah, Y. T., Yew, K. H., Hassan, M. F., and Teow, M. Y. W., Leading Sentence News TextRank. In Proceedings of 2021 International Conference on Intelligent Cybernetics Technology & Applications, pp. 92-95, 2021.
• Sim, T. Y., Teow, M. Y. W., and Lau, S. L., Unplugged Computational Thinking Activities Framework Development for Novice Programmer. In Proceedings of 2021 IEEE International Conference on Computing, pp. 297-302, 2021.
• Teow, M. Y. W., Experimenting Deep Convolutional Visual Feature Learning using Compositional Subspace Representation and Fashion-MNIST. In Proceedings of 2020 IEEE 2nd International Conference on Artificial Intelligence in Engineering and Technology, pp. 1-6, 2020.
• Phua, Y. T., Yew, K. H., Foong, O. M., and Teow, M. Y. W., Assessing Suitable Word Embedding Model for Malay Language through Intrinsic Evaluation. In Proceedings of 2020 International Conference on Computational Intelligence, pp. 202-210, 2020.
• Teow, M. Y. W., Convolutional Visual Feature Learning: A Compositional Subspace Representation Perspective. In Proceedings of 2018 International Conference on Control and Computer Vision, pp. 84-89, 2018.
• Teow, M. Y. W., Understanding Convolutional Neural Networks using A Minimal Model for Handwritten Digit Recognition. In Proceedings of 2017 2nd IEEE International Conference on Automatic Control and Intelligent Systems, pp. 165-170, 2017.