About

My name is Sy Trinh. I am currently in the process of completing my PhD at the University of Canterbury. My research focused on developing statistical models to efficiently fuse real-time traffic data from multiple sources (e.g., GPS, Bluetooth, and loop detectors) for traffic state estimation.

Before doing my PhD, I obtained a Master’s degree in Applied Data Science and another in Physics. With this background, I have a solid foundation in Mathematics, Statistics, Machine Learning and Programming. I’m proficient in Python and R programming languages and have some basis in SQL. I also have strong expertise concerning the tools required for Data Science, such as Data Analysis and Data Manipulation (NumPy, SciPy, Pandas), Data Visualization (Matplotlib, Seaborn), Machine Learning frameworks and libraries (Keras, TensorFlow, scikit-learn), and Azure cloud services for Machine Learning and Computer Vision. I’m passionate about Data Science and Machine Learning, and I love to discover hidden secrets in data to make predictions for smarter decisions in future.

This personal website is to keep track of my projects, share my ideas, and document my development in Artificial Intelligence and Data Science. Do not hesitate to contact me for questions, suggestions, and collaborations.