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 479 matching student topics
Displaying 217–228 of 479 results
Combining solar and vibration energy harvesting for rainfall prediction
Rainfall prediction plays a crucial role in various sectors such as agriculture, water resource management, and disaster preparedness. Traditional prediction methods often rely on complex meteorological models and expensive equipment. However, advancements in energy harvesting technology offer the opportunity to develop low-cost and sustainable solutions for rainfall prediction.This project proposes to leverage solar and vibration energy harvesting for rainfall prediction. Combined measurements from both solar and vibration energy harvesting can provide comprehensive data for real-time monitoring of cloud coverage and …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Information Systems
HoliCOW – A holobiont strategy to decipher core host-microbiota interactions in cows
To meet the goal of limiting global warming to 1.5C, methane emissions from ruminants such as beef and dairy cattle must be reduced by 11–30% by 2030 and by 24–47% by 2050 compared to 2010 levels. A newly funded Future Fellowship project is hiring 2 PhD students who will tackle this challenge by creating a thorough mechanistic understanding of the microbiological, biochemical and genetic processes that cause methanogenesis in the cow rumen. These activities will identify core beneficial microbiota that …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
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Centre for Microbiome Research
Avatar customisation for diversity training in virtual reality
Avatar representation is found to be crucial for user engagement in various types of applications and user identifications with avatars. This project aims to design and develop an environment where users can customize their avatars by looking at a virtual mirror. In this project, where users will be trained in diversity awareness, it is crucial for them to feel like the character who is in the scenario. The outcome of the project will be used in experiments to test the …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
SLAM inside the human body: camera tracking and 3D reconstruction for medical procedures
Minimally invasive surgery and endoscopic interventions rely heavily on the clinician’s ability to understand and navigate complex internal anatomy using only a narrow and often restrictive field of view. Having access to an accurate and dynamic 3D reconstruction of the endoscopic scene, together with reliable camera pose estimation can significantly improve spatial awareness and navigation during procedures. The generated map can be used alongside the device’s estimated location to help clinicians better orient themselves within the patient, and it also …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Physics informed machine learning for energy forecasting
Accurate forecasting is at the heart of many modern industries from energy and transport to retail, supply chains, finance, climate, and health. This research project explores deep learning approaches for time-series forecasting, investigating how modern architectures such as recurrent neural networks, LSTMs, Temporal Convolutional Networks, transformers, and multimodal foundation models can shape the next generation of forecasting systems.The overarching goal is to develop robust, interpretable, and scalable forecasting models that outperform classical methods and work effectively in real-world settings, including …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Energy Transition Centre
Hierarchical forecasting: forecasting a collection of time series
Hierarchical forecasting is a method used to generate forecasts at multiple levels of aggregation within a structured hierarchy. This technique is particularly valuable in situations where data can be organised into a hierarchy based on different dimensions, such as geography, product categories, or time. The approach ensures that forecasts at the top levels (e.g. total sales) align with forecasts at the lower levels (e.g. regional or product-level sales), creating a coherent and consistent forecasting process across the entire hierarchy.In many …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Re-localisation in natural environments
Re-localisation in robotics involves the process of determining a robot's current pose, consisting of its position and orientation. This can either be within a previously mapped and known environment (i.e. prior map) or relative to another robot in a multi-agent setup. Re-localisation is essential for enabling robots to perform tasks such as autonomous monitoring and exploration seamlessly, even when they encounter temporary challenges in precisely tracking their location in GPS-degraded environments. For instance, consider the 'wake-up' problem, where a robot …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Mapping the world: understanding the environment through spatio-temporal implicit representations
Accurately mapping large-scale infrastructure assets (power poles, bridges, buildings, whole suburbs and cities) is still exceptionally challenging for robots.The problem becomes even harder when we ask robots to map structures with intricate geometry or when the appearance or the structure of the environment changes over time, for example due to corrosion or construction activity.The problem difficulty is increased even more when sensor data from a range of different sensors (e.g. lidars and cameras, but also more specialised hardware such as …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
- Research centre(s)
- Centre for Robotics
Submarine manipulation
This project will explore and develop techniques for control and vision in submarines to allow for robust and effective manipulation capabilities - autonomous control of an underwater mobile manipulator in the presence of current and reactionary forces.Underwater maintenance: A submarine mobile manipulator can carry out underwater maintenance and monitoring, for example, dam wall maintenance or ship hull cleaning.Coral reef: A submarine mobile manipulator which can collect samples, remove rubbish, remove invasive species, and/or monitor.Alternatively, these same underlying ideas could be …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Electrical Engineering and Robotics
Fine-grained software vulnerability detection using deep learning techniques
Software vulnerability is a major threat to the security of software systems. Thus, the successful prediction of security vulnerability is one of the most effective attack mitigation solutions. Existing approaches for software vulnerability detection (SVD) can be classified into static and dynamic methods. Powered by AI capabilities, especially with the advancement of machine learning techniques, current software has been produced with more sophisticated methodologies and components. This has made the automatic vulnerability proneness prediction even more challenging. Recent research efforts …
- Study level
- PhD, Master of Philosophy
- Faculty
- Faculty of Science
- School
- School of Computer Science
Overcoming the challenges of sensitive data via synthetic data generation (case study)
In the 21st Century, there is an abundance of data, often containing insights that could benefit a number of stakeholders. However, despite this opportunity, it is often the case that the data is sensitive and can not be released by organisations or government agencies due to privacy concerns. One possible solution to the above dilemma is to instead carefully construct a 'twin' data set that contains similar information (and ideally, the same insights) as the original data set, but without …
- Study level
- Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Multi-modal sentiment analysis
In deep learning models, language models and word embedding methods have become popular to understand the context of text data. Popular language models such as BERT have limitations in terms of the token length. There exist some corpora that have longer text with an average of 1000 tokens. Additionally, these corpora are text-heavy and only include some images.In our prior works, we have developed several multi-modality models on social media datasets.
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
- Research centre(s)
- Centre for Data Science
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