Air Quality Data Analysis and Prediction Using Machine Learning Approach
Project Description

Nowadays, many powerful machine learning tools are introduced and are proven to be useful in many fields. However, due to the background knowledge gap between meteorology and computer science, meteorology field still heavily rely on simple models designed by meteorologists based on their experience and observation. Collaborating with meteorology specialists from civil engineering department, many modern machine learning methods could be applied to solve meteorology problems effectively. In this project we are focusing on the modeling and predicting the pronounced problem of air-pollution in greater China area. To provide useful insights for solving the problem.

Supervisor
NG Wilfred Siu Hung
Co-Supervisor
NG Wilfred Siu Hung
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

In this project you will be closely working with PhD students with strong research and programming skills. You will have the chance to get hands on experience with using well-known popular machine learning (deep learning) tools on a powerful GPU server, and distributed implementation of varied machine learning and data mining tools on a powerful CPU cluster with large datasets. As this project is of both research and application values, it could help in your pursuit of a higher degree or a career in the industry.

Applicant's Learning Objectives

Acquire the knowledge of GPU server and the implementation of some machine learning tools
Understand CSE research methodology

Complexity of the project
Moderate