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 10 matching student topics
Displaying 1–10 of 10 results
Big Data ideas for GLMs
The goal of this project is to develop new Bayesian methods for large-scale data analysis using subsampling techniques. The focus of the project will be on generalised linear models (GLMs), which are commonly used models in statistics and machine learning.One of the main challenges in using Bayesian statistics with big data is the high computational cost associated with processing big datasets. The proposed project aims to address this challenge by developing new subsampling techniques for Piecewise Deterministic Markov Process (PDMP) …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Mathematical Sciences
- Research centre(s)
- Centre for Data Science
Investigating smart campus development trends in Australian universities
Smart campus is an emerging concept following the smart city research movement and is predominantly argued to be a miniature replica of the smart city providing an ideal prototype for university campus development. The smart campus concept has attracted much attention, predominantly due to the rise in artificial intelligence, internet-of-things, cloud computing and big data applications in advancing university campus operation efficiency. In recent years, Australian universities started to invest in smart campus technologies and development opportunities.ReferenceA brief background on …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Symbiosis in microbial ecosystems
Soil systems are fundamentally important to the health of our planet, but the complexity of soil microbial communities makes them particularly challenging to study. Soil systems are amongst the most diverse microbial ecosystems on Earth in terms of the number of microbial species (and strains) present within individual samples, and in the breadth of functions encoded. Beyond complexity measured by counting distinct community members, interactions between microbial species including symbiosis, parasitism or commensalism are widespread and yet barely studied.
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
- Research centre(s)
-
Centre for Microbiome Research
Investigating the application of sustainable AI practices in construction
The construction industry plays a vital role in the global economy and there is a growing interest in utilising artificial intelligence (AI) to improve its productivity and efficiency. Despite the industry's significant contribution to the economy, it has faced challenges such as large cost overruns, extended schedules, and quality concerns. Nevertheless, AI is making significant strides to remove these issues by revolutionising various aspects of the construction industry. This is evident from enhancing project planning and design to improving construction …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Architecture and Built Environment
Light, circadian rhythms and Parkinson’s disease
Up to 98% of patients with Parkinson’s Disease (PD) have non-motor symptoms (Poewe et al. Nature Rev Dis 2017, 3: 17013) and of those, circadian and sleep disorders are the most common (for review, Gros & Videnovic. 2020, Clin Geriatr Med 36: 119). These symptoms become increasingly prevalent during the course of PD and are key determinants affecting quality of life, advancement of overall disability and placement in nursing homes (Shapira et al. Nat Rev Neurosci 2017,18:435). Circadian and sleep …
- Study level
- PhD
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Big data analysis to aid ecological research
We're looking for multiple students to help us answer the question: 'How can we utilise information technology to aid ecological research?'Sensor networks bring ecologists and pattern recognition researchers together to make some applications possible. These applications include assessing risks from potential bird collisions, unobtrusive observations (where the presence of humans changes some animal behaviours) and studying spatial and temporal variation in biological processes.With a significant amount of data being collected from these applications, processing and mining this data is challenging. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
Transport big data analytics: Imputing missing data
The missing data problem is often unavoidable for real-world data collection systems because of a variety of factors, such as sensor malfunctioning, maintenance work, transmission errors, and so on. Filling in missing information in a dataset is an important requirement for many machine-learning algorithms that require a complete dataset as input. Data imputation algorithms aim at filling the missing information in a dataset. Many missing data imputation techniques exist in the literature, with applications demonstrated on various types of datasets. …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Leveraging Big Data and AI/ML for Smart Transport Solutions
This PhD position aims to harness the potential of big traffic and mobility data alongside cutting-edge AI/ML algorithms to pioneer innovative solutions for optimizing smart motorways and/or arterial traffic flow. By leveraging these technologies, the project endeavours to develop and test smart algorithms, with the goal of significantly enhancing the efficiency and safety of road networks.Send via email to Prof. Ashish Bhaskar (ashish.bhaskar@qut.edu.au):a brief statement detailing your suitability for the positiona detailed curriculum vitae, including a list of publications, if …
- Study level
- PhD
- Faculty
- Faculty of Engineering
- School
- School of Civil and Environmental Engineering
- Research centre(s)
- Centre for Data Science
Prostate cancer transcriptomics (Honours and Master of Philosophy)
At the Australian Prostate Cancer Research Centre QLD, we are interested in the cellular adaptive response processes leading to therapy resistance in advanced prostate cancer.A focus area of our research is studying the transcriptome changes in prostate cancer cell lines, xenograft models and patient samples using RNA sequencing technologies.By integrating our large in-house repository of RNAseq data sets with publicly available studies, this project will further explore the cellular heterogeneity of prostate tumours and the plasticity of cancer cells in …
- Study level
- Master of Philosophy, Honours
- Faculty
- Faculty of Health
- School
- School of Biomedical Sciences
Human data interaction with big data visual analytics
Our research is seeking to answer the question: 'How can we support human interaction with big data?'We want to integrate the outstanding capabilities of humans in terms of visual information exploration with the enormous processing power of computers. These elements have the capacity to form a powerful knowledge discovery environment. This research will use datasets from the Queensland Government and the QUT Ecoacoustic research group over multiple years. Other big datasets, such as Amazon’s product review dataset, could also be …
- Study level
- PhD, Master of Philosophy, Honours
- Faculty
- Faculty of Science
- School
- School of Computer Science
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