Teaching
Artificial Intelligence (Postgraduate)
This module provides an overview of techniques used in Artificial Intelligence including agent modelling, problem formulation, search, logic, probability and machine learning.
Deep Learning for Audio and Music (Postgraduate)
This module, for those who have some prior knowledge of machine learning, focusses on deep learning methods and how they can be used to address many tasks in audio and music. The theory of modern deep neural networks (DNNs) is covered, including training of common DNN types as well as modifying DNNs for new purposes. Various tasks in analysis/generation of audio and music are studied directly to inspire the content, using raw audio and/or symbolic representations. Background in machine learning is essential, and some background in digital signal processing is highly recommended. Music knowledge would be desirable but is not a requirement.
Risk and Decision-Making for Data Science and AI (Postgraduate)
This module provides a comprehensive overview of the challenges of risk assessment, prediction and decision-making covering public health and medicine, the law, government strategy, transport safety and consumer protection. Students will learn how to see through much of the confusion spoken about risk in public discourse, and will be provided with methods and tools for improved risk assessment that can be directly applied for personal, group, and strategic decision-making. The module also directly addresses the limitations of big data and machine learning for solving decision and risk problems.
Research
Research Interests:
I investigate topics in the fields of machine learning/deep learning and signal processing. I am particularly interested in audio/speech analysis, biosignal analysis, and healthcare applications.