QUT offers a diverse range of student topics for Honours, Masters and PhD study. Search to find a topic that interests you or propose your own research topic to a prospective QUT supervisor. You may also ask a prospective supervisor to help you identify or refine a research topic.
Found 50 matching student topics
Displaying 1–12 of 50 results
PSYC05 - Using EEG to investigate how the brain represents objects while they are temporarily invisible
In vision, objects are frequently occluded behind other objects, such as when a dog walks behind a fence. How does the brain represent objects that are either wholly or partially invisible? This project investigates this using an advanced new EEG analysis technique that we recently developed to decode the brain's visual predictions. We have previously used this new technique to show that the brain predicts what you are going to see, to allow you to see them more quickly, and …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
PSYC03 - Predicting the present: investigating motion extrapolation mechanisms in the human brain
It takes time for our brains to process the signals coming from our eyes. Without compensating for this delay, we would be unable to perceive and interact with objects in real-time. For example, assuming a delay of just 70 ms (less than a 10th of second), a professional tennis player facing a 190 km/h serve should see the ball 3.6 m behind its true position. So how, then, can they accurately hit it? The aim of this project is to …
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Health
- School
- School of Psychology and Counselling
Transforming media industries
The Transforming Media Industries research program in the Digital Media Research Centre investigates how the business practices and cultural dynamics of media industries are adapting to profound transformations in the production, distribution, consumption, and regulation of media content in local and global contexts. We examine the operations of power and the potential for innovation, focusing especially on the implications they pose for media makers, the media they make, and their social consequences across the film, television, games, music, news, and …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Creative Industries, Education and Social Justice
- School
- School of Communication
- Research centre(s)
- Digital Media Research Centre
Analysis of professional squash matches
This project concerns computer vision and statistical analysis of performance in professional level matches in the game of squash.The goal is to use computer vision and existing systems to capture and analyse patterns of play, allowing coaches and professional players to develop strategies to improve performance, to counter particular types of play and even to tailor game plans to attack individual opponents.
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
Sport AI
Videos of sport activities are widely available at large scales. AI and its sub-fields, especially computer vision and machine learning, have a great potential to analyse, understand and extract useful information from these videos.This project aims at using AI and its subfields in computer vision and machine learning to develop techniques for analysing sport videos to extract intelligence for players and coaches.
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Understanding responsible deployment of computer vision for urban planning
Advances in artificial intelligence (AI) offer urban planning practice many novel prospects. By the responsive use of AI, planners can effectively analyse data, improve processes, increase efficiency, and prioritise human-centric aspects of planning to develop sustainable cities. Computer vision is one of the key areas where responsible AI is applied in urban planning to revolutionise the analysis and interpretation of visual data, like images and videos captured in cities to aid decision and plan making processes. While the potential impacts …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Conversational agents that can see
The development of conversational agents, whether as smart home devices, or embedded in mobile devices or social robots, has started in the world of chatbots, with only text available, and then started to build audio features, and finally considering context through sensors and cloud knowledge, as well as offering images in response to a query.However, little attention has been paid to other conversational modalities, such as showing, pointing, or gesturing. The reliance on these is exacerbated in conversation with people …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Artificial Intelligence for collaborative and intelligent user interfaces
This project seeks to leverage recent advances in machine vision and natural language processing algorithms to support the design and development of knowledge-driven applications that support communication and collaborations with their users.One particular area where this will be investigated is in workplaces for supported employment, that is employment opportunities for people with intellectual disability. One of the questions to address is how machines could respond to what a user shows them in order to assist with decision making in a …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Drone and satellite Artificial Intelligence
Satellite and drone/UAV data has a great potential to provide large-scale analytics for many domain applications. However, the wide range of data of diverse nature (e.g., optical vs. SAR, high-resolution vs. wide-coverage, mono- vs. hyper-spectral, 2-D vs. 3-D) also poses significant challenges for analytics.Deep learning holds great promise to deal with these tasks. While the number of research in this area is increasing, there still exists challenges such as co-learning of multimodal data, limited data annotation, and uncertainty in the …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Automated abnormality detection in endoscopy data
The project focus on developing an artificial intelligence system for automated abnormality detection of endoscopy data. Developing a model for abnormality detection would leverage the capacity to aid medical practitioners in precisely detecting abnormalities by reducing the mistakes that happen via human error. This project will develop an image-based method using deep learning techniques to perform the classification of various abnormalities that can occur within the gastrointestinal tract, such as ulcerative colitis, esophagitis etc.
- Study level
- Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Physics-informed machine learning
Recent advances in computer vision have demonstrated superhuman performance on a variety of visual tasks including image classification, object detection, human pose estimation and human analysis. However, current approaches for achieving these results center around models that purely learn from large-scale datasets with highly complex neural network architectures. Despite the impressive performance, pure data-driven models usually lack robustness, interpretability, and adherence to physical constraints or commonsense reasoning.As in the real world, the visual world of computer vision is governed by …
- Study level
- PhD, Master of Philosophy, Honours, Vacation research experience scheme
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Machine learning for understanding and predicting behaviour
Understanding behaviour and predicting events is a core machine learning task, and has many applications in areas including computer vision (to detect or prediction actions in video) and signal processing (to detect events in medical signals).While a large body of research exists exploring these tasks, a number of common challenges persist including:capturing variations in how behaviours or events appear across different subjects, such that predictions can be accurately made for previously unseen subjectsmodelling and incorporating long-term relationships, such as previously …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
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