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Explainable AI-enabled predictive analytics for decision making support

Modern predictive analytics, underpinned by AI-enabled learning (such as machine learning, deep learning) techniques, has become a key enabler to the automation of data-driven decision making.In the context of business process management, predictive analytics makes predictions about the future state of a running business process instance. These predictions can include:which task will be carried out nextwhen the task be carried outwho will perform the taskwhen an ongoing process instance will be completewhat the outcome will be upon completion.Machine learning models …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Information Systems
Research centre(s)
Centre for Data Science

Neuroscience-based algorithms for robotics and autonomous vehicles

Increasingly, researchers are looking to neuroscience and the brain for inspiration in how they design their deep learning network architectures for robotics and artificial intelligence tasks.This project will design innovative new neural network-based learning approaches to make breakthroughs in robotic and autonomous vehicle capabilities in:sensingscene understandingvisual place recognitionnavigationSimultaneous Localisation And Mapping (SLAM)other key capabilities.In doing so you will gain invaluable experience and skills in one of the most exciting fields in the world today, along with opportunities for international travel …

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)

Visual memory summarisation for life-long mobile service robots operation in everyday environments

This research project aims to answer the question: How can video summarisation methods be used for efficient review and data storage of visual sensory data captured during a life-long operation of mobile service robot?Video summarisation refers to the process of generating a summary that best conveys the most informative content of a longer video.

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

Performance monitoring of deep learning models for robotic perception

This project breaks the current 'weak' assumption in the literature that the performance of deep learning models reported on a holdout dataset is an indicator of the performance on all future and yet to be encountered conditions during deployment. In reality, performance fluctuates and can drop below critical thresholds when the robot travels through particular places, times and conditions.

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

Human-in-the-loop techniques to debug machine learning models

Machine learning models are being deployed in critical domains such as healthcare, education and fintech. The current approach to deploying machine learning models is based on considering a data-centric approach where the models are evaluated using performance measures on a test set. However, the high performance of the model on test data is not indicative of its reliability,An important aspect of reliability is in the understanding of what exactly a machine learning model encodes, and to verify if it learns …

Study level
PhD, Master of Philosophy, Honours, Vacation research experience scheme
Faculty
Science and Engineering Faculty
School
School of Information Systems
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)

Lifelong semantic mapping of large scale environments

When building a map of objects inside a real environment, this map can become quickly outdated as objects are moved around over time. This is especially true when the map is on the scale of a house, warehouse or a city.This PhD project investigates new methods for keeping a high-resolution semantic map up-to-date using partial, and possibly low-resolution, snapshots. These environment snapshots can be captured by sensors mounted on moving agents, such as vehicles and mobile robots. …

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

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