PROF. DR. LOO CHU KIONG
Department of Artificial Intelligence
Faculty of Computer Science and Information Technology
ckloo.um@um.edu.myView CV | |
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Biography | |
Prof. Dr. Loo has conducted fascinating research over the last eight years in The University of Malaya, particularly in addressing the central problem of Artificial Intelligence about continual learning without catastrophic forgetting. His numerous publications on the topic have been well-received and have made a substantial contribution to the kernel-based theoretical framework for Adaptive Resonance Theory. He has published more than 200 peer-reviewed journal and conference papers on neurorobotics and machine intelligence. In high-impact journals such as IEEE Transactions on Neural Networks and Learning Systems, Neural Networks, Journal of Neural Systems, IEEE Transactions on Cognitive and Developmental Systems, IEEE Transactions on Cybernetics, to name a few. Prof. Loo is also the recipient of JSPS fellowship award from Japan and the Georg Forster Fellowship award from Humboldt Foundation, Germany. He has been the visiting professor of University of Prefectural Osaka University, Japan, and King Mongkut's Institute of Technology Ladkrabang, Thailand. He has applied the developed theory to medical diagnosis, prognosis, and neurorobotics, and the potential of his research findings has been successfully demonstrated in various domains, including digital healthcare and cognitive robotics. Chu Kiong has been recognized for his excellence in applied research that has commercial potential based on the 10 patents filed. He is one of the founders of UM spin-off company, UMCH Sdn. Bhd. specializing in AI-enabled connected healthcare solutions. Moreover, he is honoured Malaysia’s Research Star Award 2019 - Research and Innovation Excellence Awards, from the Ministry of Education as one of the most influential researchers in Malaysia. He received the Top Research Scientist Malaysia (TRSM) award 2020 from the Academy of Science Malaysia. |
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Finance
Grant | Progress | Status |
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IIRG002C-19HWB |
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CSRG008-2020ST |
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PPSI-2020-CLUSTER-IDIG01 |
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This information is generated from Research Grant Management System |