10+ Publication in top AI/ML conferences including NeurIPS/ICML/ICLR/AAAI
2017 – Tan Siu Lin Scholarship, DTZ/Cushman & Wakefield Scholarship
2016 – Canon Scholarship

My research focuses on designing machine learning models for data of complex structures, such as graphs. As a member of the Foundation, I will continue my research to push the boundaries of graph machine learning and design algorithms with more expressiveness, guaranteed robustness and higher interpretability. I also aim to apply machine learning models to real-world applications including creating a general-purpose robotic system with multi-task solving ability and advancing biomedical knowledge discovery. I very much look forward to collaborating with other members to achieve my goal, which is to design accessible, open, unbiased AI that will ultimately benefit humankind.