Machine Learning for Environmental Applications
Project Description

Machine learning is often used to fuse and integrate large amounts of heterogeneous data from many different sources to deliver smart/expert analysis or prediction. In this project, students will be asked to apply current machine learning techniques to conduct research on a selected topic from a suite of environmental problems.

Supervisor
LAU Alexis Kai Hon
Co-Supervisor
FUNG Jimmy Chi Hung
Quota
5
Course type
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

Applicants, in consultation with the faculty supervisor, shall first choose a research topic from a suite of environmental problems ((including climate risk analysis, extreme weather prediction, air quality forecasts, real-time location and personalize exposure analysis, smart building energy-saving and environmental improvement, lifestyle and health risks, … etc.). Then, using machine learning techniques, the applicant shall try to improve the expert analysis or prediction important for the chosen research topic.

Applicant's Learning Objectives

Applicants shall get a much more comprehensive understanding of different machine learning techniques, as well as applying some of them to help address a real-life environmental problem.

Complexity of the project
Moderate