Dr Xianghua Xie
Associate Professor
Computer Science
Telephone: (01792) 602916
Email: JavaScript is required to view this email address.
Room: Office - 510
Fifth Floor
Faraday Building (Tower Block)
Singleton Campus

Dr. Xie currently is an Associate Professor, leading a research team on Computer Vision and Medical Image Analysis, in the Visual Computing Group at the Department of Computer Science, Swansea University. He was holding an RCUK Academic Fellowship between September 2007 and March 2012, and he was a Senior Lecturer between October 2012 and March 2013. Prior to his position at Swansea, He was a Research Associate in the Computer Vision Group, Department of Computer Science, University of Bristol, working on a European Commission project, CASBliP.

Dr. Xie received his M.Sc. degree (with commendation) in Advanced Computing in 2002 from the University of Bristol, UK. Then, he continued to pursue a Ph.D. degree in the same department from the end of 2002, under the supervision of Prof. Majid Mirmehdi. Prof. Barry Thomas was also involved in cosupervision at the earlier stage. He finished his Ph.D. study in March 2006.

Dr. Xie has strong research interests in medical imaging and image analysis, biomedical applications, video analysis, stereo systems, active contour models, level set methods, texture analysis, and pattern recognition and machine learning. He is leading a team of researchers in these areas and more details can be found from his group website: http://csvision.swan.ac.uk

Areas of Expertise

  • Computer Vision
  • Image Processing
  • Pattern Recognition
  • Machine Learning
  • Big Data
  • Medical Image Understanding
  • Medical Imaging

Publications

  1. & Recurrent Neural Networks for Financial Time-Series Modelling. Presented at International Conference on Pattern Recognition,
  2. & 3D mesh segmentation via multi-branch 1D convolutional neural networks. Graphical Models 96, 1-10.
  3. & Automatic segmentation of cross-sectional coronary arterial images. Computer Vision and Image Understanding 165, 97-110.
  4. & (2017). Learning Feature Extractors for AMD Classification in OCT Using Convolutional Neural Networks. Presented at Signal Processing Conference (EUSIPCO), 2017 25th European, Kos: Signal Processing Conference (EUSIPCO), 2017 25th European. doi:10.23919/EUSIPCO.2017.8081167
  5. & AMD Classification in Choroidal OCT using Hierarchical Texton Mining. Presented at Advanced Concepts for Intelligent Vision Systems,

See more...

Teaching

  • CS-M87 MRes Visual Computing Project

    This module is the project phase of the MRes degree in Visual Computing.

  • CSC345 Big Data and Machine Learning

    This model 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.

  • CSC770 Visual Computing Project Development

    In this module students will be presented with an overview of the research area of Visual Computing. They are introduced into the topic, the background and the aims of their project. They write a detailed specification which will be the basis of their research project. Guidance as to appropriate research methodologies is provided.

  • CSCM10 Computer Science Project Research Methods

    This module will introduce students to some fundamental research methodologies and good practice in research. They will undertake background research including a literature review and specify the aims of their MSc project.

  • CSCM30 Research Methods and Seminars

    This module will introduce students to some fundamental research methodologies and good practice in Data Science. They will undertake background research including a literature review and specify the aims of their Data Science project, as well as produce a plan for their proposed research.

  • 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.

  • CSCM77 Computer Vision and Pattern Recognition

    This module introduces students to the important and modern topics and concepts of computer vision and pattern recognition, including image processing, segmentation, feature extraction, camera calibration, stereo vision, motion analysis, object tracking, recognition, data clustering, and dimensionality reduction. It teaches techniques that are used to understand and interpret the contents of images and videos and dissects state-of-the-art vision systems, such as Microsoft Kinect. Practical examples in C++ with OpenCV library and Matlab are provided throughout the lectures

  • CSDM03 Computational Thinking skills for Digital Social Scientists.

    This module will discuss some of the most widely used and artificial intelligence and machine learning, regression & clustering techniques and their applications to big data social science questions. The students will gain and understanding of both strengths and weaknesses of learning and practical know-how in applying those theories to real world problems. Topics include big social data concepts, data mining, learning theories, supervised and unsupervised learning, and reinforcement learning.

Supervision

  • Representation Learning in Irregular Domains. (current)

    Student name:
    PhD
    Other supervisor: Prof Mark Jones
  • Using novel data types for epilepsy research using big data, free texts and genetic analysis. (current)

    Student name:
    PhD
    Other supervisor: Dr Seo-Kyung Chung
    Other supervisor: Prof Mark Rees
  • 3D Meshes Segmentation (current)

    Student name:
    PhD
    Other supervisor: Dr Gary Tam
  • Artificial Intelligence and the steel industry - development of an automated quality inspection system (current)

    Student name:
    EngD
    Other supervisor: Dr David Penney
  • n.a. (current)

    Student name:
    MRes
    Other supervisor: Dr Adeline Paiement
  • Adopting data driven modelling and prediction approaches to support strategies for successful game outcomes in Rugby (current)

    Student name:
    MSc
    Other supervisor: Dr Matthew Roach
  • Estimating Left Ventricle Displacement Due To Heartbeat Using Manifold Learning and Deep Learning (current)

    Student name:
    MRes
    Other supervisor: Dr Adeline Paiement
  • Untitled (current)

    Student name:
    PhD
    Other supervisor: Dr Gary Tam
  • Data Visualisation and Data Mining/Pattern Recognition for Biological Data. (current)

    Student name:
    PhD
    Other supervisor: Prof Mark Jones
  • 4D reconstruction of solar active regions from multi-spectral images using deep learning (current)

    Student name:
    PhD
    Other supervisor: Dr Adeline Paiement
  • Large scale characterisation of galaxy morphology: a deep learning approach (current)

    Student name:
    PhD
    Other supervisor: Dr Adeline Paiement
  • Irregular Domain Deep Learning (current)

    Student name:
    PhD
    Other supervisor: Dr Gary Tam
    Other supervisor: Mr Michael Edwards
  • Visualisation and Machine Learning. (current)

    Student name:
    PhD
    Other supervisor: Prof Mark Jones
  • Shape co-analysis and correspondences (preliminary title) (current)

    Student name:
    PhD
    Other supervisor: Dr Gary Tam
  • Unravelling Polypharmacy: Determining interaction patterns between medications using complex electronic health records for better patient care. (current)

    Student name:
    PhD
    Other supervisor: Dr Shang-Ming Zhou
  • Higher dimensional colour mapping and transfer functions for image and volume data (provisional) (current)

    Student name:
    PhD
    Other supervisor: Prof Mark Jones
  • 'Deep Learning Methods for Texture Analysis in Medical Imaging' (awarded 2018)

    Student name:
    MSc
    Other supervisor: Dr Adeline Paiement
  • 'Adaptive Learning for Segmentation and Detection. ' (awarded 2017)

    Student name:
    PhD
    Other supervisor: Dr Gary Tam

Administrative Responsibilities

  • Foundation year head - Department of Computer Science

    2011 - Present

  • Programme Coordinator - MRes in Visual Computing

    2010 - Present

  • Programme Coordinator - MSc by Research in Visual Computing

    2011 - Present

  • Programme Coordinator - MSc with specialism in Visual Computing

    2011 - Present

  • Recruitment and Admissions - MRes in Visual Computing

    2008 - Present

  • Recruitment and Admissions - MSc by Research in Visual Computing

    2011 - Present

  • Recruitment and Admissions - MSc with specialism in Visual Computing

    2011 - Present

  • General Teaching Management - University and Subject Statistics

    2010 - Present

  • Engagement and Impact Committee (co-opted) - University and Subject Statistics

    2010 - Present

  • Seminar Coordination - Department of Computer Science

    2008 - 2010

Career History

Start Date End Date Position Held Location
April 2013 Present Associate Professor Department of Computer Science, Swansea University
October 2012 March 2013 Senior Lecturer Department of Computer Science, Swansea University
September 2007 September 2012 Lecturer (RCUK Academic Fellow) Department of Computer Science, Swansea University
August 2007 September 2007 Research Associate Department of Computer Science, Bristol University
February 2006 July 2007 Research Assistant Department of Computer Science, Bristol University
February 2011 November 2005 Research Assistant and PhD Student Department of Computer Science, Bristol University

External Responsibilities

  • Associate Editor, IET Computer Vision

    2012 - 2015

  • Chair and co-chair, BMVC, MIUA, BMVA, RIVIC, ICPRAM, CMBE, EPSRC

    2008 - 2015

  • Executive Committee, British Machine Vision Association

    2012 - Present

  • Steering Committee, Medical Image Understanding and Analysis

    2011 - Present

  • Organising Committee, CMBE, PSM

    2009 - 2013

  • Keynote: "Deformable Model in Segmentation and Tracking", AMDO

    2012 - Present

  • Conference Tutorial, SITIS

    2007 - Present

  • International Programme Committee, ***

    2012 - Present

  • Journal referee, ****

    2012 - Present

  • External examiner: MSc in Computational and Software Techniques, Cranfield University

    2013 - 2016

  • External PhD examiner, ****

    2012 - Present

  • Lead Researcher, NISCHR Faculty

    2013 - Present

  • Member, IEEE and BMVA

    2002 - Present

Key Grants and Projects

  • Biomedical Research Unit: Advanced Medical Image Analysis and Visualisation, Collaborator 2011 - 2015

    led by Prof. John (Bangor University), Funded by NISCHR, £325K to Swansea (£1.5M in total)

  • Non-Invasive Quantification of Complex Heart Valve Lesions: A model-based approach using 3D echocardiography, Co-investigator 2011 - 2014

    led by Dr. van Lool (Swansea University), Funded by NISCHR, £58K

  • Patient Specific Multi-view Coronary Geometry and Computational Disease Modelling, Principal investigator 2010 - 2012

    , Funded by WORD, £144K

  • NISCHR Registered Research Group: Medical Image Analysis and Visualisation, Co-investigator 2010 - 2013

    led by Prof. Zwiggelaar (Aber University), Funded by NISCHR, £95K

  • Wales Research Institute on Visual Computing (RIVIC), I am leading a sub-programme on 3D Vision and Medical Image Analysis 2009 - 2013

    , Funded by WAG, £5M

  • PRINS: Prior-independent Shape Regularisation for Geometric Active Contours, Co-investigator 2006 - 2008

    led by Prof. Mirmehdi (Bristol University), Funded by The Leverhulme Trust, £65K

Research Groups