Chee Chan is a Full Professor at Universiti Malaya leading a research team in computer vision and machine learning with nine years of professional experience and a PhD in Artificial Intelligence from the University of Portsmouth. He is a principal architect of ILMU, Malaysia’s first sovereign multilingual LLM, and led development of MalayMMLU, the world’s first Bahasa Melayu benchmark—work that has helped integrate homegrown AI into regulated domains such as banking (e.g., Ryt AI). His scholarship and leadership have earned national and international recognition, including the TRSM award, a Hitachi Research Fellowship, and membership in the Young Scientists Network of the Academy of Sciences Malaysia. Beyond academia, he has served in national science policy roles at MOSTI and supported pandemic response efforts, demonstrating an ability to translate research into public impact. As Associate Editor for Pattern Recognition and a collaborator with WeBank, he bridges rigorous research, industry collaboration, and responsible AI deployment. Notably, his work emphasizes preserving linguistic and regulatory context in AI systems—ensuring local values shape scalable, real-world technologies.
9 years of coding experience
Doctor of Philosophy (Ph.D.), Artificial Intelligence, Doctor of Philosophy (Ph.D.), Artificial Intelligence at University of Portsmouth
ArtGAN + WikiArt: This work presents a series of new approaches to improve GAN for conditional image synthesis and we name the proposed model as “ArtGAN”.
Contributions:177 commits, 6 PRs, 157 pushes in 5 years 10 months
Code repo for ICME 2020 paper "Style-Conditioned Music Generation". VAE model that allows style-conditioned music generation.
Contributions:11 commits, 9 pushes in 1 year 5 months
music-generationdeep-learningvaeconditionedmusic
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