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Honours and Minor Thesis projects

Displaying 51 - 60 of 220 honours projects.


Primary supervisor: Benjamin Tag

This project aims to extend the existing knowledge on emotion regulation, looking to detect the impact of extrinsic regulation experiences in immersive environments on players and spectators. We will apply a multimodal sensing approach to detect emotional changes in the player using biometric data (electrodermal activity, heart rate, speech analysis, eye movement, pupil dilation), movement signals, and conscious emotional experiences.

Primary supervisor: Benjamin Tag

This is a research-heavy project, looking for students with an interest in human behaviour and data analysis.

Primary supervisor: Benjamin Tag

In this project, we will look into how to make the physiological data of VR users visible to externals, e.g., a teacher watching a student learning in VR, or a supervisor watching a worker fulfil a task in VR.

Different studies have shown that fluctuations in cognitive load are expressed through changes in human physiology, such as temperature patterns on the face or pupil dilation. However, in users of VR headsets, the face and eyes are covered by the HMD.

Primary supervisor: Benjamin Tag

Human Perception and Cognition in Visualization is a field of research that focuses on understanding how people perceive and understand visual representations of data. Many questions about how investigating visual representations of data can influence user perceptions, decision-making, and memory, are unanswered.

Primary supervisor: Ron Steinfeld

Recently, program generation and optimisation techniques have been adapted to performance critical subroutines in cryptography. Codes generated/optimised by these techniques are both secure and their performance is highly competitive compared to hand-optimised code by experts [1].

 

Primary supervisor: Benjamin Tag

The global health crisis has put mental health, emotional well-being, and the risks and importance of digital technologies into the global focus. According to a Lancet Commission report, the number of people with mental disorders is increasing in every country of the world and will cost the global economy US$16 trillion by 2030. Emotions have strong implications not only for mental well-being but also for physical health, e.g., down-regulating negative emotions can lower the risk of heart disease.

Primary supervisor: Chunyang Chen

Software testing is a crucial part of the software development process, ensuring that the developed software is of high quality and meets the requirements of the users. However, testing can be a complex and time-consuming task, especially when it comes to testing software in multiple languages. ChatGPT is trained in multiple languages, making it easier for understanding and detect bugs in multilingual software.

Primary supervisor: Chunyang Chen

Product teams always need to conduct a user study with real and targeted users once the product is developed to test the usability and potential bugs in the products; however, this process is always time-consuming and costly. The team may need to find people of different backgrounds, train them, and then spend time with the users when they are doing the study. Moreover, they always need to conduct several rounds of usability tests every time they iterate the product based on the feedback from the previous study or because of the new requirements from product managers.

Primary supervisor: Chunyang Chen

Jupyter notebooks have become a popular platform for data scientists to develop and test their code. However, as the number of code cells and markdown cells increase in a notebook, it can become challenging to maintain code quality and refactoring. While integrated development environments (IDEs) like PyCharm and VSCode have code assistants like Copilot, these features are not widely available in Jupyter notebooks.

Primary supervisor: Chunyang Chen

Recently, large language models (LLM) gained popularity for their emerging powerful capabilities. For example, when given appropriate prompts, they could execute a task following instructions or demonstrations. In this project, we focus on generating chain-of-thought (CoT) prompts, using a codebank filled with basic sketches, to measure LLMs’ ability in automatic debugging.