People
The Razer-NUS Joint AI Research Laboratory brings together academic and industry leadership across artificial intelligence, multimedia systems, game intelligence, and real-world product translation.
Co-Directors
Ooi Wei Tsang
Computer Science, NUS
Ooi Wei Tsang is an Associate Professor in the Department of Computer Science at NUS Computing and a co-director of the Image & Pervasive Access Lab. He received his B.Sc. from NUS and his Ph.D. in Computer Science from Cornell University, then spent a year as a postdoctoral fellow at the Berkeley Multimedia Research Center before joining NUS. His research spans interactive and networked multimedia applications, with current interests including volumetric video streaming, networked virtual environments, cloud gaming systems, Edge AI, and human-AI interaction. His work has received recognitions including NUS Computing teaching awards and awards at ACM Multimedia and ACM TOMCCAP.
Wee Hong Jie
Razer
Dr Wee Hong Jie is Director of AI Software at Razer, where he leads the company's AI software team, driving Razer's software-side AI initiatives across the business. His work involves leading the development of first in industry AI Gaming products by applying frontier AI and productionising them, as seen in Razer AVA and QA Companion-AI.
Dr Wee brings a strong research foundation to his role, having completed his doctoral degree at Nanyang Technological University, specialising in the field of computer science, artificial intelligence, human factors and air traffic management. This background informs his approach to designing human-centred AI systems.
Principal Investigators
Yan Shuicheng
Computer Science, NUS
Yan Shuicheng is a Distinguished Professor (Practice Track) at the NUS School of Computing. He received his B.S. and Ph.D. from Peking University and previously served as Group Chief Scientist at Sea Group, alongside other senior industry roles. His research focuses on computer vision, machine learning, and multimedia analysis, and his listed interests include efficient, executive, and evolving AGI. He is a Fellow of the Singapore Academy of Engineering, AAAI, ACM, IEEE, and IAPR, and has been recognised repeatedly as one of the world's Highly Cited Researchers.
Qizhe Xie
Computer Science, NUS
Qizhe Xie is an Assistant Professor in the Department of Computer Science at NUS. He earned his Master's and Ph.D. from Carnegie Mellon University and his bachelor's degree from Shanghai Jiao Tong University, and he also spent two years conducting research at Google DeepMind, previously Google Brain. His research interests include large language models, deep learning, and natural language processing. He has worked on semi-supervised learning methods including Noisy Student and UDA, contributed to the RACE reading-comprehension benchmark, and served as an area chair for major AI and machine learning conferences including NeurIPS, ICML, and ICLR.