NUS Graduate School for Integrative Sciences and Engineering


RI Supervisor
Research Areas
Brief Description of Research
1. Computer Science
2. Artificial Intelligence
3. Deep Learning
4. Machine Learning
5. Computational Biology
6. Multimedia Analysis and Retrieval
7. Video Retrieval


The research of my group is mostly on computer vision, machine learning, and its biomedical applications. One key application area is 3D camera based pose estimation, tracking, and activity/behavior analysis of articulated objects (such as human hand and upper body, lab mouse, and zebrafish). So far we have obtained one of the best academic results on 3D camera based hand pose estimation, as published in top venues such as (ICCV13, IJCV16, IJCV17), and demonstrated at international (ICCV13 demo sessions) and national venues (poster award at A*STAR Scientific Conference, and demos at Singapore Science festival, as well as A*STAR Research Highlights). Another application focus area is on 2D/3D filamentary structured image (such as neuronal images, vascular images) segmentation and reconstruction. For example, we have participate in the BigNeuron Initiative ( where our 3D neuron segmentation method has so far achieved one of the top performance. Our related work has been published at top-tier venues (MICCAI14, TMI16, TMI17, TPAMI17) and have also been into A*STAR Research Highlights. On general machine learning and computer vision side, we have also works in various informatics and analytics aspects (TPAMI16, SIAMSC16, AAAI16).