Rate My Professor Hong Lim

Chern Hong Lim is a Senior Lecturer in the Malaysia School of Information Technology at Monash University. He earned his Ph.D. in Computer Science, majoring in Artificial Intelligence, from the University of Malaya between 2011 and 2015, with a thesis titled 'Fuzzy Qualitative Approach for resolving uncertainty in Human Motion Analysis.' He also obtained his B.Sc. (Hons) in Computer Science, majoring in Artificial Intelligence, from the University of Malaya from 2007 to 2010. Before his current role, Lim served as Senior Lecturer at Tunku Abdul Rahman University College from 2016 to 2018, Senior Associate Researcher at Telekom Research & Development Sdn Bhd from 2014 to 2015, and Visiting Researcher at the University of Portsmouth in the computer vision domain.

Lim's research interests encompass artificial intelligence, machine learning, computer vision, image processing, and fuzzy logic, with ongoing emphasis on Explainable AI, Cognitive Video Analysis, and medical imaging. As Chief Investigator, he leads projects such as a comprehensive end-to-end intelligent platform for brain tumor diagnosis, treatment, and recurrence monitoring (2025–2027), WAge: Healthy Working environments for all ages (2023–2027), novel cross-reactive aptamers against cobra venom cytotoxins (2023–2026), RewardQNet for untreated intracranial aneurysm segmentation (2022–2026), and DELTA: Inclusive Teletherapy (2022–2024). His contributions align with UN Sustainable Development Goal 3: Good Health and Well-being. Key publications include 'Fuzzy human motion analysis: A review' (Pattern Recognition, 2015), 'Deepfake attribution: On the source identification of artificially generated images' (Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery, 2022), 'The role of artificial intelligence in the battle against antimicrobial-resistant bacteria' (Current Genetics, 2021), 'Amogel: a multi-omics classification framework using associative graph neural networks...' (BMC Bioinformatics, 2025), and 'CSTA: Spatial-Temporal Causal Adaptive Learning for Exemplar-Free Video Class-Incremental Learning' (IEEE Transactions on Circuits and Systems for Video Technology, 2025). His scholarship has accumulated over 545 citations on Google Scholar. Lim has earned the 'Belt and Road' Young Scientists Exchange Award (2024) and a Gold Medal at ITEX 2021 for 'BAITRADAR - A clickbait detection deep learning architecture for Youtube.' He is active in the IEEE Computational Intelligence Society Malaysia Chapter, has organized conferences including ICIRA2020 and APSIPA 2017, and judges AI hackathons and competitions.