Researched and designed multiple prediction models to recognize hand gestures using data from Inertial Measurement Unit
Collected dataset of hand gestures and tested the prediction models on the dataset using pandas and scikit-learn packages
Integrated the model within the Robotic Operating System (ROS) framework to be used in robots
Deep Learning Research Intern
DSO Information Systems Department
Researched and designed a deep-learning multi-task CNN model using Pytorch for attribute prediction to assist in person re-identification across non-overlapping cameras
Presented to the head of the Information Systems department on the findings and applicability of such model in their overall project
Self-learnt the knowledge of implementing and optimizing CNN across multiple deep-learning frameworks within 2 months of the internship
Education
PhD Mobile Robotics
Singapore University of Technology and Design
Thesis on Context-Aware Perception in Adverse Conditions. Supervised by Prof Malika Meghjani. Presented papers at 4 IEEE conferences with the contributions being published in 6 IEEE proceedings. Awarded with the President’s Graduate Fellowship
Computer Science and Design
Singapore University of Technology and Design
GPA: 4.44/5.0
Bachelors of Engineering (Hons)
Awarded with the SUTD Merit Scholarship