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Found 17 matching student topics

Displaying 1–12 of 17 results

Technology, Innovation and Health

Professor Belinda Bennett is interested in talking to students who wish to undertake research on legal issues related to technology, innovation and health, regulation of innovative health technologies, legal issues related to genomics, the use of artificial intelligence in health care, and the use of robotics in health care.

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

Australian Centre for Health Law Research

Gesture-based control of underwater helper-bots

Underwater robotic systems have been in use for several decades. In recent years, various groups have been adding manipulators and other payloads to increase their utility. However, their role has primarily been monitoring and mapping the oceans without human interaction.The next frontier is to have human divers and robotic system collaborate safely and productively in the same space to jointly complete complex tasks. This will involve the robotic system directly understanding and interacting with the diver in a non-verbal manner. …

Study level
PhD, Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Coordinated control of multi-robot systems for environmental management

Single robotic systems can't accurately measure dynamic processes and map large areas in challenging environments. However, managing multiple robotic systems simultaneously poses many challenges around coordination and control. This is particularly true in environments where there's a lack of communication with the system. This project will explore multi-robot swarming and formation control to monitor, manage and track large-scale environmental phenomena.In this project, you will explore multi-robot swarming and coordinated formation control for dynamic process monitoring, target tracking and coordinated mapping. …

Study level
PhD, Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Robotics

Advanced artificial intelligence based ultrasound imaging applications

Our research in the space of advanced quantitative medical imaging is investigating how to use ultrasound as a real time volumetric mapping tool of human tissues, to guide in a reliable and accurate way complex medical procedures1. We have developed several novel methods which make use of the most cutting-edge artificial intelligence technology2. For example, to show where the treatment target and the organs at risk are at all times during treatments in radiation therapy3, 4; or to inform robots …

Study level
PhD, Master of Philosophy
Faculty
Faculty of Health
School
School of Clinical Sciences
Research centre(s)
Centre for Biomedical Technologies

The Challenge of Neural Interfaces to Law

Dr Scott Kiel-Chisholm is looking for PhD/MPhil candidates considering the legal dimensions from the development and adoption of neural interfaces. We are interested in looking for candidates looking at civil and criminal implications, comparative legal analysis and the legal and quasi-legal implications of neural interfaces for supra-legal institutions like the WTO and the EU. This topic is led by the QUT School of Law within the Datafication and Automation of Human Life research group.

Study level
PhD, Master of Philosophy, Honours
Faculty
Faculty of Law
School
School of Law
Research centre(s)

Augmented reality (AR) applications for robotic scene understanding

Augmented reality (AR), or mixed reality, has become a mature technology with many possible practical applications in manufacturing, retail, navigation and entertainment.We're interested in using AR to support human-robot interaction. In this project, you'll investigate how a human can use AR to better understand how a robot perceives the world and to understand the robot's intentions.

Study level
Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Electrical Engineering and Robotics
Research centre(s)

Deep learning for robotics in open-world conditions

To fully integrate deep learning into robotics, it's important that deep learning systems can reliably estimate the uncertainty in their predictions. This allows robots to treat a deep neural network like any other sensor and use the established Bayesian techniques to fuse the network’s predictions with prior knowledge or other sensor measurements or to accumulate information over time.Deep learning systems typically return scores from their softmax layers that are proportional to the system’s confidence. They are not calibrated probabilities and …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Electrical Engineering and Robotics
Research centre(s)

HR and Robotics

The 2018 Robotics Roadmap for Australia suggests a range of ways that robotics may affect the business world.  In particular, humans may need to work alongside robots or their efforts may be augmented by robots.  For this project the focus is on the HR implications of the various ways humans and robots may interact in the workplace.

Study level
Vacation research experience scheme
Faculty
QUT Business School
School
School of Management
Research centre(s)

Biofabrication robotics and meta-material research

Biofabrication is the application of advanced manufacturing (AM) to medicine. Part of our research involves the design and construction of AM tools to aid in tissue engineering, 3D scanning, computational medicine and 3D printing solutions for several healthcare needs.

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Mechanical, Medical and Process Engineering
Research centre(s)

Reimagining Aged-care Furniture: A cradle to cradle approach through mass customisation

Reimagining Aged-care Furniture: A cradle to cradle approach through mass customisationAdvancements in robotic manufacturing processes present new opportunities for the realisation of aged care furniture, but require research in design and fabrication, end-user input, product lifecycle management and materials research. Addressing IFE’s Centre for a Waste Free World, this project aims to pilot a cradle to cradle approach to reimagine aged care furniture by creating a user-centered design to fabrication workflow in collaboration with industry partners Healthcraft Furniture, UAP, and …

Study level
Vacation research experience scheme
Faculty
Creative Industries Faculty
School
School of Design
Research centre(s)

Design Lab

Machine learning for wildlife monitoring

This project will investigate methods to monitor wildlife using machine learning applied to aerial imagery.While it's highly desirable to use drones and aerial footage to monitor wildlife, there are substantial challenges created by the nature of the data and target wildlife.This, combined with the vast nature of any collected aerial data, makes manual analysis difficult. This challenge motivates the development of machine learning methods to automatically process data and perform tasks, such as:detecting target animalscounting herd animalsclassifying land useassessing environment …

Study level
Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Electrical Engineering and Robotics
Research centre(s)
Centre for Data Science

The insufficient informativeness of measurements in Bayesian detection problems

Shiryaev's Bayesian Quickest Change Detection (QCD) problem is to detect a change in the statistical problems of an observed process. This is an important signal processing problem with application in a diverse range of areas, including:automatic controlquality controlstatisticstarget detection.Recently a critical deficiency in Shiryaev's QCD problem has been identified to occur due to the insufficient informativeness of measurement in low signal-to-noise (SNR) to overcome geometric prior assumption on the change event.These deficiencies are due to the non-ergodic nature of the …

Study level
PhD
Faculty
Science and Engineering Faculty
School
School of Electrical Engineering and Robotics
Research centre(s)

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