Publications

  1. Edwards, M., Xie, X., PALMER, R., Tam, G., Alcock, R., Roobottom, C. Graph convolutional neural network for multi-scale feature learning Computer Vision and Image Understanding

Teaching

  • CS-150 Concepts of Computer Science 1

    This module along with CS-155 gives an overview of some of the main principles underlying computers and computing from both a theoretical and an applied point of view. Following a brief history of computers and software an introduction to the representation of data and the basic components of a computer will be given. Students will be introduced to the principles of programming at assembly language level. The module is accessible and relevant to students of all disciplines who wish to learn about, or reinforce their understanding of, computers and computer science.

  • CS-155 Concepts of Computer Science 2

    This module follows on from CS-150 and gives an overview of some of the main principles underlying computers and computing from both a theoretical and an applied point of view. Topics discussed include simple algorithm analysis, operating systems, file systems, computer networks, the world wide web, and some basic issues of computer security. A brief discussion on the limitations of computing is also given. The module is accessible and relevant to students of all disciplines who wish to learn about, or reinforce their understanding of, computers and computer science.

  • CSC345 Big Data and Machine Learning

    This module provides a broad introduction to artificial intelligence, machine learning, pattern recognition, and their applications to big data problems. The students will gain understanding and knowledge of the theoretical foundations of learning, learn effective machine learning techniques, and acquire practical know-how in applying some of those theories and techniques to real world problems. Topics include big data concept, data mining, learning theories, supervised and unsupervised learning, and reinforcement learning.

  • CSC364 Software Testing

    Testing is the process of systematically experimenting with an object (the SUT = System Under Test) in order to establish its quality, where quality means the degree of accordance to the intention or specification. This module will cover various test scenarios; practical exercises will allow the students to gain hands-on experience.

  • CSCM45 Big Data and Machine Learning

    This module will discuss in-depth some of the most widely used and state-of-the-art artificical intelligence and machine learning techniques and their applications to big data problems. The students will gain both theoretical understanding of learning and practical know-how in applying those theories to real world problems. Topics include big data concept, data mining, learning theories, supervised and unsupervised learning, and reinforcement learning.

  • CSCM64 Software Testing

    Testing is the process of systematically experimenting with an object (the SUT = System Under Test) in order to establish its quality, where quality means the degree of accordance to the intention or specification. This module will provide an in-depth introduction to various test scenarios and enable students to gain hands-on experience by means of a number of practical exercises.

Supervision

  • Irregular Domain Deep Learning (current)

    Student name:
    PhD
    Other supervisor: Dr Gary Tam
    Other supervisor: Prof Xianghua Xie
  • Untitled (current)

    Student name:
    PhD
    Other supervisor: Dr Daniel Archambault