Climate Risk Identification using natural language processing
Project Description
Climate risks can be classified as primary, secondary, and tertiary with increasing complexity. Tertiary risks are non-linear interactions between environmental variables that are not well known, and thus very difficult to mitigate. Tertiary impacts are often the ones with the most severe consequences to society. The project is related to the use of Natural Language Processing techniques to collect or “listen in” on the tertiary impacts that take place around the world and to build a global Climate Risk Database for future use.
LAU Alexis Kai Hon
Course type
Applicant's Roles
Work with senior researchers to try out various subjective (manual) and objective (including AI and other natural language processing methods) techniques to identify climate risks, and develop the specification of the proposed Climate Risk Database.
Applicant's Learning Objectives
The students will develop the ability to design research activities and then carry them out to support a clearly defined research objective. They would also develop the ability to face unexpected situations during their research activities.
Complexity of the project