AI for evaluating the project's carbon credit.
Project Description
Currently evaluating carbon credit is time-consuming and data intensive to support green finance. This project aims to test the feasibility of applying AI to evaluate the project's carbon credit. This is a cross-disciplinary project across data science and environmental sustainability to produce deliverables to finance. If you are interested in this project, please consider finding a team member to cover both data science and environmental sustainability. You can send me emails for details.
Supervisor
LU Zhongming
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles
Develop a database of projects receiving carbon credit.
Identify critical features of projects receiving carbon credit.
Apply AI algorithms to examine the feasibility of predicting carbon credit.
Identify critical features of projects receiving carbon credit.
Apply AI algorithms to examine the feasibility of predicting carbon credit.
Applicant's Learning Objectives
Understand the need of carbon credit.
Practice the quantitative analytical skills.
Enhance the cross-disciplinary culture and system thinking.
Practice the quantitative analytical skills.
Enhance the cross-disciplinary culture and system thinking.
Complexity of the project
Moderate