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Found 23 matching student topics

Displaying 1–12 of 23 results

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

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

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

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

Advancing monitoring of diverse grass pollen with computer vision

We're seeking a motivated student to join the multidisciplinary project that brings together computer vision and deep learning field with pollen aerobiology. This is a fully funded PhD program for a three-year period starting in 2024. It's part of the project funded by the Australian Research Council Discovery Program—Digitally-Integrated Smart Sensing of Diverse Airborne Grass Pollen Sources. The successful candidate will be primarily based in the Allergy Research Group at QUT's Kelvin Grove campus.Grass pollen is the main outdoor allergen …

Study level
PhD
School
School of Biomedical Sciences
Research centre(s)
Centre for Robotics
Centre for Immunology and Infection Control

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
School
School of Electrical Engineering and Robotics

New technology and the law

Computer vision has developed to a point where machines using artificial intelligence are better and faster than humans at performing many vision-related tasks. For example, we are now often processed through customs based solely on face recognition software. Add to this the fact that the average Australian is photographed on CCTV cameras around 75 times per day. Commercial applications of face recognition technology include Microsoft's Face Application Programming Interface that can be used to classify face images based on gender, …

Study level
PhD, Master of Philosophy
School
null
Research centre(s)
null
null

Assessing visual acuity errors in pre-school children (CVER01)

Measuring visual acuity is in preschool children is challenging. In particular, young children will be prone to making mistakes in identifying symbols on eye charts, even when they can see what those symbols are, so called “false negative responses”.This project uses an established vision assessment protocol, EVA testing, and assesses the extent of false negative responses in this task. The protocol assesses the effects of an intervention, pointing to the target on a card, which may decrease false negative responses. …

Study level
PhD
Faculty
Faculty of Health
School
School of Clinical Sciences
Research centre(s)

Centre for Vision and Eye Research

Evidence-driven policy innovation for urban heat islands

Extreme heatwaves and other extreme weather events are contributing to the fragility of cities and urban infrastructure, which requires urgent attention. Urban heat islands are an exemplar for metropolitan fragile areas, which exacerbate the impact of climate change and global warming on natural hazards, such as wildfires, storms, floods, and droughts, which pose a critical threat to Australian and international communities (Degirmenci et al., 2021). Decision support systems (DSS) can help city planners and policymakers to optimise their decision-making by …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Business and Law
School
School of Management
Research centre(s)
Centre for Future Enterprise

Prescriptive process analytics

With growing significance of data there is a need to harness the potential of that data for improved business operations. Historical data is often to provide a descriptive overview of how business processes have performed in the past. However, there is a need to be proactive and take appropriate actions to ensure that business processes perform in an optimal manner. Prescriptive analytics is a process that analyzes data and provides instant recommendations on how to optimize business practices. Prescriptive analytics …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Information Systems

Modelling and managing uncertain Antarctic species networks

Antarctic ecosystems are complex, and data is limited since it is expensive to collect. Species including penguins, seabirds, invertebrates, mosses, and marine species interact in food webs which can be modelled as mathematical networks. These networks can be large, span across terrestrial and marine systems, and are changing in response to environmental changes.These ecological networks can be modelled using differential equation predator prey models like Lotka-Volterra to describe these interactions. However, the relationships between species are not always known, or …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

Optimal conservation management in uncertain Antarctic environments

Species and ecosystems in Antarctica are threatened. Optimal biodiversity conservation is an interdisciplinary field combining mathematical modelling and optimisation with ecology and conservation. We can use mathematics to understand the system, model how management actions might impact it, and then optimise which actions should be used. For example, we can explore where protected areas should be placed, how species should be managed, or how tourist impacts should be reduced. However, the complexities of conservation in Antarctica necessitate the application of …

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Science
School
School of Mathematical Sciences
Research centre(s)
Centre for Data Science
Centre for the Environment

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