Projects per year
Personal profile
Biography
Mei Kuan LIM is a lecturer attached to the School of Information Technology at Monash University Malaysia. She graduated from Universiti Malaysia Sarawak, Malaysia in 2007 with a First Class Honours in Computer Science. In 2015, she received her Doctoral degree from University of Malaya, Malaysia, under the scholarship of Yayasan Khazanah. She further completed her post-doctoral studies in the Department of Artificial Intelligence in the University of Malaya until 2016. Previously, she was a researcher in MIMOS Berhad from 2004 to 2007, conducting research and development in video surveillance, in particularly intelligent video analytics solutions. She was also a visiting researcher in Kingston University, United Kingdom in 2012 and 2013. Her research interests include swarm intelligence, data and video analytics, computer vision and machine learning. She has also served as reviewer for several conferences and journals, and as an organizing committee in several conferences such as ACPR 2015 and VCIP 2013.
Research interests
Her primary research focus is in applying Artificial Intelligence algorithms, in particularly utilizing the Swarm Intelligence approaches to understand and solve problems in complex systems. She is currently engaged in social media analytics, utilizing visual and textual information to analyse the underlying behaviours of social media that may in turn lead to collective intelligence.
Monash teaching commitment
- FIT1051 - Programming Fundamentals in Java
- FIT9131 - Programming Foundations in Java
- FIT3199 - Industry Work Experience
- FIT5122 - Professional Practice
Education/Academic qualification
Computer Vision , Doctor of Philosophy, Universiti Malaya (University of Malaya)
Award Date: 19 Oct 2015
Research area keywords
- Computer Vision
- Swarm Intelligence
- Data & Video Analytics
Network
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Cognitive Neural Network (CoNNet): A novel interpretable video surveillance framework for crime scene understanding based on attributes learning
Lim, C. H., Goh, K. M., Mei Kuan, L. & Tao, Z.
1/11/20 → 31/10/23
Project: Research
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Sense-ED: Developing mobile sensing and Natural Language Processing models to support the identification of, and interventional mechanisms for, eating disorder relapse
McNaney, R., Delir Haghighi, P., Mei Kuan, L., Phan, R., Chun Yong, C., Wang, T., Sharp, G. & Bell, B. T.
Monash University – Internal Faculty Contribution
19/08/21 → 31/08/22
Project: Research
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An integrated CNN-LSTM based model for predicting mental health risk using social media data
Mei Kuan, L., Seng Chan, C., Kok, V. J., Chun Yong, C. & Sing Kiat, T.
1/11/20 → 31/10/22
Project: Research
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A comprehensive overview of deepfake: Generation, detection, datasets, and opportunities
Seow, J. W., Lim, M. K., Phan, R. C. W. & Liu, J. K., 7 Nov 2022, In: Neurocomputing. 513, p. 351-371 21 p.Research output: Contribution to journal › Article › Research › peer-review
2 Citations (Scopus) -
An optimal vehicle counting framework for non-CCTV placements
Hooi, N. C., Chee Pin, E. T., Shiong, C. Y. & Kuan, L. M., 2022, Proceedings of 2022 APSIPA - Annual Summit and Conference Chiang Mai, Thailand November 7-10, 2022. Mankong, U. (ed.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 846-852 7 p. (Proceedings of 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2022).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Fairness evaluation in deepfake detection models using metamorphic testing
Pu, M., Kuan, M. Y., Lim, N. T., Chong, C. Y. & Lim, M. K., 2022, Proceedings - 7th International Workshop on Metamorphic Testing, MET 2022. Xie, X., Kanewala, U. & Donaldson, A. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 7-14 8 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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Metamorphic testing-based adversarial attack to fool deepfake detectors
Lim, N. T., Yi Kuan, M., Pu, M., Lim, M. K. & Yong Chong, C., 2022, 2022 26th International Conference on Pattern Recognition, ICPR 2022. Jenkin, M., I. Christensen, H. & Liu, C-L. (eds.). Piscataway NJ USA: IEEE, Institute of Electrical and Electronics Engineers, p. 2503-2509 7 p. (Proceedings - International Conference on Pattern Recognition; vol. 2022-August).Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
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On the application of machine learning models to assess and predict software reusability
Yeow, M. Y. H., Chong, C. Y. & Lim, M. K., 2022, Proceedings of the 6th International Workshop on Machine Learning Techniques for Software Quality Evaluation. Cordy, M., Xie, X., Xu, B. & Stamatia, B. (eds.). New York NY USA: Association for Computing Machinery (ACM), p. 17-22 6 p.Research output: Chapter in Book/Report/Conference proceeding › Conference Paper › Research › peer-review
1 Citation (Scopus)