Centre of Data Science and Artificial Intelligence projects
Projects for 2024/2025
201—Data Science and Artificial Intelligence for Aquaculture
This large project seeks 5 individual excellent summer scholars from current third-year and fourth-year students in AIML, DATA, COMP/SWEN with AI specialisation to carry out research in data science and AIML for the New Zealand aquaculture industry. The successful scholars/students will use/develop DSAI, machine learning, and computer vision algorithms and techniques to support decision-making in the NZ aquaculture industry for responding to climate challenges, managing fish disease, improving fish production yields, and fish farming sustainably at scale.
A good background in Python programming and COMP 307/COMP 309 is required. A good background in statistics/optimisation would be preferred. The successful scholars/students will work with one of the experienced supervisors in the Centre for Data Science and AI— Mengjie Zhang, Ivy Liu, Bing Xue, Richard Arnold, Yi Mei, Bin Nguyen, and Fangfang Zhang. The students/scholars will be located at Victoria University of Wellington and are expected to generate/submit a paper/prototype.
Supervisors
Director, Centre of Data Science and Artificial Intelligence
Centre for Data Science and Artificial Intelligence
Deputy Head of School, Engineering and Computer Science
School of Engineering and Computer Science
Council Member
Deputy Head of School
Vice-Chancellor's Office|School of Mathematics and Statistics
Programme Director, Computer Science & Computer Graphics
School of Engineering and Computer Science
Lecturer, Artificial Intelligence
Centre for Data Science and Artificial Intelligence
203—Help Save Lives! Genetic Programming for Ambulance Dispatch
In 2019, research from the U.S. Government suggested that a 60-second reduction in the national ambulance response time would save 10,120 lives per year. Every second counts to save more lives!
Sponsored by a NZ$1 million Ministry of Business, Innovation, and Employment (MBIE) Smart Idea Fund and collaborating with Wellington Free Ambulance, this project aims to improve ambulance dispatch decisions and reduce ambulance response time through machine learning and genetic programming. You may choose from one of two research topics:
- Improving the emergency dispatch simulation, for example, by making it more efficient and accurately represent reality.
- Improving the core decision-making by developing and testing a novel genetic programming algorithm.
You should be adept at mathematics and coding with Java. Ideally, you will also have experience using genetic programming and solving combinatorial optimization problems. If the summer project goes well, we can discuss continuing it through an honours, Master's, or PhD project.
Supervisor
Programme Director, Computer Science & Computer Graphics
School of Engineering and Computer Science
204—Evolutionary Machine Learning for King Salmon Health Prediction
King salmon is the only salmon species farmed in New Zealand and plays an important role in its aquaculture. Different features, such as temperature and feeding frequency, can affect the farming of king salmon. If we can predict the healthy status of king salmon well and solve the health issues earlier, it would be great for king salmon production. Evolutionary machine learning, such as genetic programming, has shown its advantages for king salmon health classification tasks.
This project will focus on using evolutionary machine learning to accurately predict whether a king salmon is healthy or not. We are interested in which aspects of information are important for healthy prediction. The student is expected to work at Victoria University of Wellington. We will provide preprocessed data and code in Python that has already been established for students to continue working on. This project will be co-supervised by Professor Bing Xue and Professor Mengjie Zhang.
Supervisors
Lecturer, Artificial Intelligence
Centre for Data Science and Artificial Intelligence
Deputy Head of School, Engineering and Computer Science
School of Engineering and Computer Science
Director, Centre of Data Science and Artificial Intelligence
Centre for Data Science and Artificial Intelligence