- Harnessing computer vision technologies for public good as part of the video analytics team in the Data Science and Artificial Intelligence Division (DSAID), under the Technology Associate Program.
Work Experience
- Improved performance of advertisement moderation model pipelines through the investigation and implementation of new training methodologies and algorithms from areas such as metric learning, semi-supervised learning, and face forgery detection, using Python and PyTorch, as part of the monetization integrity team.
- Built development tools to facilitate data cleaning, fast model iteration, and streamlined model development pipeline.
- Implemented autonomous data acquisition and annotation pipeline using depth, tracking and infrared cameras on a Raspberry Pi-mounted drone, pseudo-labelling, and semi-supervised learning, reducing data collection and annotation time by 90%.
- Trained and deployed detection, segmentation and tracking models in an iterative and incremental manner using PyTorch and TorchServe on AWS EC2 for Agri-tech specific tasks, ensuring high mean average precision and throughput.
Education
- Awarded the Lee Kuan Yew Gold Medal for being the top student in the cohort.
- Awarded Dean's List for all eligible years, ranking in top 5% of cohort with a GPA of 4.97/5.00 (Honors – Highest Distinction).