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Chee Seng Chan

Chee Seng Chan, Prof., PhD

College of Engineering and Computer Science

Affiliate Faculty

Biography

Professor Chan is a Full Professor at Universiti Malaya, Malaysia, with over a decade of experience in academic leadership, research development, and international collaboration in artificial intelligence and computer science. His academic career spans senior roles including Head of Department, Deputy Dean (Research and Development), and Dean at Universiti Malaya. Beyond academia, he served at the Ministry of Science, Technology and Innovation (MOSTI) as Undersecretary for Data Strategic and Foresight, contributing to national-level initiatives in data governance and technology planning during a critical period of public service.

Professor Chan has led and secured competitive research funding from national and international agencies, serving as Principal Investigator for projects spanning computer vision, machine learning, medical AI, and privacy-preserving systems. His work emphasizes methodological rigor, responsible AI design, and real-world applicability across domains such as healthcare, security, and digital systems. He has been actively involved in professional service within the global research community. He was the founding Chair of the IEEE Computational Intelligence Society (Malaysia Chapter) and has played key leadership roles in organizing major international conferences, including IEEE VCIP 2013, ACPR 2015, IEEE MMSP 2019, and ACM Multimedia Asia 2025.

In addition to his research contributions, Professor Chan has supervised postgraduate researchers and supported cross-institutional academic exchange across Asia and beyond. As an Affiliate Professor, his role focuses on fostering collaborative research, mentoring graduate students, and strengthening long-term research partnerships between institutions.

  • Trustworthy and responsible artificial intelligence
  • Machine unlearning and lifecycle-aware foundation models
  • Computer vision and multimodal representation learning
  • Evaluation and benchmarking of foundation models, particularly in low-resource and multilingual settings
  • Applied AI for regulated and safety-critical domains

  • Artificial Intelligence
  • Machine Learning
  • Computer Vision,
  • Image Processing
  • Research Methodology

  • Ong, W.K. and Chan, C.S. “Maverick: Collaboration-free Federated Unlearning for Medical Privacy”, 28th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI), Sept., 2025. (oral, acceptance rate = 2.2%)
  • Fan, T. et al. (2025). “Ten Challenging Problems in Federated Foundation Models”, IEEE Transactions on Knowledge and Data Engineering (TKDE), vol. 37(7), pp. 4314 – 4337.
  • Chua, X.J., Tan, J., Tan, J.X., Poh, S.C., Goh, Y.X., Yang, S. J., … & Chan, C. S. “Banking Done Right: Redefining Retail Banking with Language-centric AI”, Conference on Empirical Methods in Natural Language Processing (EMNLP), Nov., 2025.
  • Sii, J.W. and Chan, C.S. (2025). “Gorgeous: Creating narrative-driven makeup ideas via image prompts”, Multimedia Tools and Application (MTA), pp. 1-22.
  • Lin, C.T., Ng, C.C., Tan, Z.Q., Nah, W.J., Wang, X., Kew, J.L., …, Chan, C.S., and Zach, C. (2025). “Text in the Dark: Extremely Low-light Text Image Enhancement”, Signal Processing: Image Understanding (SP:IC), vol. 130, pp. 117222.
  • Gu, H. Ong, W.K., Chan, C.S. and Fan, L. “Ferrari: Federated Feature Unlearning via Optmizing Feature Sensitivity”, Thirty-eighth Annual Conference on Neural Information Processing Systems (NeurIPS), Dec., 2024.
  • Hoe, J.T., Jiang, X., Chan, C.S., Tan, Y.P. and Hu, W. “InteractDiffusion: Interaction-Control for Text-to-Image Diffusion Model”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June, 2024.
  • Ng, C.C., Lin, C.T., Tan, Z.Q., Wang, X., Kew, J.L., Chan, C.S., and Zach, C. (2024). “When IC meets Text: Towards A Rich Annotated Integrated Circuit Text Dataset”, Pattern Recognition (PR), vol. 147, p.110124.
  • Poh, S.C., Yang, S. J., Tan, J., Chieng, L., Tan, J.X., … & Chan, C. S. “MalayMMLU: A Multitask Benchmark for the Low-resource Malay Language”, Conference on Empirical Methods in Natural Language Processing (EMNLP), November, 2024.
  • Ng, K.W., Zhu, X., Hoe, J.T., Chan, C.S., Zhang, T., Song, Y.Z., and Xiang, T. “Unsupervised Hashing with Similarity Distribution Calibration”, 34th British Machine Vision Conference (BMVC), Aberdeen, U.K., November, 2023. (oral, acceptance rate = 7.5%)
  • Lin, C.T., Kew, J.L., Chan, C.S., Lai, S.H. and Zach, C. (2023). “Cycle-object Consistency for Image-to-image Domain Adaptation”, Pattern Recognition (PR), vol. 138, p.109416.
  • Ooi, X.P. and Chan, C.S. “LLDE: Enhancing Low-light Images with Diffusion Model”, IEEE International Conference on Image Processing (ICIP), Kuala Lumpur, Malaysia, October 2023.
  • Nah, W.J., Ng, C.C., Lin, C.T., Lee, Y.K., Kew, J.L., Tan, Z.Q., Chan, C.S., Zach, C. and Lai, S.H. “Rethinking Long-tailed Visual Recognition with Dynamic Probability Smoothing and Frequency Weighted Focusing”, IEEE International Conference on Image Processing (ICIP), Kuala Lumpur, Malaysia, October 2023.
  • Tan, Z.Q., Wong, H.S. and Chan, C.S. “An Embarrassingly Simple Approach for Intellectual Property Rights Protection on Recurrent Neural Networks”, Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (AACL-IJCNLP), November 2022. (oral long paper, acceptance rate = 15.7%)
  • Fan, L., Ng, K.W., Chan, C.S. and Yang, Q. (2022) “DeepIPR: Deep Neural Network Ownership Verification with Passports”, IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), vol. 44(10), pp. 6122-6139.
  • Tan, J.H., Chan, C.S., and Chuah, J.H. (2022) “End-to-End Supermask Pruning: Learning to Prune Image Captioning Models”, Pattern Recognition (PR), vol. 122, pp. 108366.
  • Beh, J.C., Ng, K.W., Kew, J.L., Lin, C.T., Chan, C.S., Lai, S.H. and Zach, C. “CyEDA: Cycle-Object Edge Consistency Domain Adaptation”, IEEE International Conference on Image Processing (ICIP), Bordeaux, France, October 2022.
  • Lim, S.W., Chan, C.S., Faizal, E.R.M. and Ewe, K.H. “ProX: A Reversed Once-for-All Network Training Paradigm for Efficient Edge Models Training in Medical Imaging”, IEEE International Conference on Image Processing (ICIP), Bordeaux, France, October 2022.
  • Lim, J.H., Chan, C.S., Ng, K.W., Fan, L., and Yang, Q. (2022) “Protect, Show, Attend and Tell: Empowering Image Captioning Models with Ownership Protection”, Pattern Recognition (PR), vol. 122, pp. 108285.
  • Hsu, P., Lin, C-T., Ng, C.C., Kew, J.L., Tan, M.Y., Lai, S-H., Chan, C.S. and Zach, C. “Extremely Low-light Image Enhancement with Scene Text Restoration”, 26th International Conference on Pattern Recognition (ICPR), Aug., 2022.
  • Hoe, J.T., Ng. K.W., Zhang, T., Chan, C.S., Song, Y-Z. and Tao, X. “One Loss for All: Deep Hashing with a Single Cosine Similarity based Learning Objective”, Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS), Dec., 2021.
  • Ong, D.S., Chan, C.S., Ng, K.W., Fan, L. and Yang, Q. “Protecting Intellectual Property of Generative Adversarial Networks from Ambiguity Attack”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), June, 2021.
  • Lim, J.Q. and Chan, C.S. “From Gradient Leakage to Adversarial Attacks in Federated Learning” IEEE International Conference on Image Captioning (ICIP), Anchorage, Alaska, USA, Sept. 2021.
  • Lim, J.H., Tan, C.S., Chan, C.S., Welikala, R.A., Remagnino, P., Rajendran, S., Kallarakkal, T.G., et. al. “D’OraCa: Deep Learning-based classification of Oral Lesions with Mouth Landmark Guidance for Early Detection of Oral Cancer”, 25th UK Conference on Medical Image Understanding and Analysis (MIUA), Oxford, U.K, 2021. (Best Student Paper Award)
  • Fan, L., Ng, K.W., Ju, C., Zhang T. and Chan, C.S. “Deep Polarized Network for Supervised Learning of Accurate Binary Hashing Codes”, International Joint Conference on Artificial Intelligence (IJCAI), Yokohama, Japan, 2020.
  • Lim, Y.Q., Chan, C.S. and Loo, F.Y. “Style-conditioned Music Generation” IEEE International Conference on Multimedia and Expo (ICME), London, U.K., July 2020. (Top 10% papers)
  • Wang. X., Liu, Y., Shen, C., Ng, C.C., Luo, C., Jin, L., Chan, C.S., Hengel, A.v. and Wang, L. “On the General Value of Evidence, and Bilingual Scene-Text Visual Question Answering”, IEEE International Conference on Computer Vision and Pattern Recognition (CVPR), Washington, USA, June, 2020.
  • Fan, L., Ng, K.W. and Chan, C.S. “Rethinking Deep Neural Network Ownership Verification: Embedding Passports to Defeat Ambiguity Attacks”, Thirty-third Conference on Neural Information Processing Systems (NeurIPS), Vancouver, Canada, Dec., 2019.
  • Tan, J.H., Chan, C.S. and Chuah, J.H. (2019) “COMIC: Compact Image Captioning with Attention”, IEEE Transactions on Multimedia (TMM), vol. 21(10), pp. 2668-2696.
  • Loh, Y.P. and Chan, C.S. (2019) “Getting to Know Low-light Images with The Exclusively Dark Dataset”, Computer Vision and Image Understanding (CVIU), vol. 178, pp. 30-42.
  • Lee, S.H., Chan, C.S. and Remagnino, P. (2018) “Multi-Organ Plant Classification based on Convolutional and Recurrent Neural Network”, IEEE Transactions on Image Processing (TIP), vol. 27(9), pp. 4287-4301.
  • Kok, V.J. and Chan, C.S. (2017) “GrCS: Granular Computing based Crowd Segmentation”, IEEE Transactions on Cybernetics (TCy), vol. 47(5), pp. 1157-1168.
  • Hoo, W.L. and Chan, C.S. (2015) “Zero-shot Object Recognition System based on Topic Model”, IEEE Transactions on Human-Machine Systems (THMS), vol. 45(4), pp. 518-525

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