Professor
Computer Science
Telephone: (01792) 513391
Email: JavaScript is required to view this email address.
Room: Office - 305
Third Floor
Faraday Building (Tower Block)
Singleton Campus

Professor Mark W. Jones is a data scientist with areas of expertise in photon mapping, ray tracing, global illumination, visualization, kernel density estimation, accelerometry data, transfer functions, probability density functions, clustering, Monte-Carlo techniques, statistics, distance measures, Lloyd’s relaxation, Voronoi diagrams, vector/chamfer distances, volume rendering, data structures (kd-trees).

Areas of Expertise

  • Ray Tracing; Global Illumination; Data Visualization; Data Science; Medical Imaging; Volume Visualization; Computer Graphics

Publications

  1. & Towards Visual Exploration of Large Temporal Datasets. Presented at 2018 International Symposium on Big Data Visual Analytics (BDVA), Konstanz, Germany:
  2. & A Deep Convolutional Auto-Encoder With Embedded Clustering. Presented at 2018 IEEE International Conference on Image Processing (ICIP), Athens, Greece, 2018, Megaron Athens International Conference Centre, Athens, Greece: 25th IEEE International Conference on Image Processing (ICIP).
  3. & A Deep Learning Approach to No-Reference Image Quality Assessment For Monte Carlo Rendered Images. Presented at Computer Graphics and Visual Computing (CGVC) 2018,
  4. & (2017). Data Painter: A Tool for Colormap Interaction. Presented at Computer Graphics & Visual Computing (CGVC) 2017, doi:10.2312/cgvc.20171280
  5. & (2017). An Automatic Laser Scanning System for Accurate 3D Reconstruction of Indoor Scenes. Presented at 2017 IEEE International Conference on Information and Automation (ICIA),2017 IEEE International Conference on Information and Automation (ICIA). doi:10.1109/ICInfA.2017.8079017
  6. & Analysis of reported error in Monte Carlo rendered images. The Visual Computer 33(6-8), 705-713.
  7. & Recognition, Tracking, and Optimisation. International Journal of Computer Vision
  8. & Implementing generalized deep-copy in MPI. PeerJ Computer Science 2, e95
  9. et. al. A spherical-plot solution to linking acceleration metrics with animal performance, state, behaviour and lifestyle. Movement Ecology 4(1)
  10. & TimeNotes: A Study on Effective Chart Visualization and Interaction Techniques for Time-Series Data. IEEE Transactions on Visualization and Computer Graphics 22(1), 549-558.
  11. & Prying into the intimate secrets of animal lives; software beyond hardware for comprehensive annotation in ‘Daily Diary’ tags. Movement Ecology 3(1)
  12. & Step by step: reconstruction of terrestrial animal movement paths by dead-reckoning. Movement Ecology 3(1)
  13. & TimeClassifier - A Visual Analytic System for the Classification of Multi-Dimensional Time-Series Data. The Visual Computer 31(6-8), 1067-1078.
  14. & DynaMoVis: Visualization of dynamic models for urban modeling. The Visual Computer 31(6-8), 1079-1088.
  15. & A new perspective on how humans assess their surroundings; derivation of head orientation and its role in ‘framing’ the environment. PeerJ 3(e908), 1-29.
  16. & A Visualization Tool Used to Develop New Photon Mapping Techniques. Computer Graphics Forum 34(1), 127-140.
  17. & FSPE: Visualization of Hyperspectral Imagery Using Faithful Stochastic Proximity Embedding. IEEE Geoscience and Remote Sensing Letters 12(1), 18-22.
  18. & Order of Magnitude Markers: An Empirical Study on Large Magnitude Number Detection. IEEE Transactions on Visualization and Computer Graphics 20(12), 2261-2270.
  19. & Transformation of an Uncertain Video Search Pipeline to a Sketch-Based Visual Analytics Loop. IEEE Transactions on Visualization and Computer Graphics 19(12), 2109-2118.
  20. & InK-Compact: In-Kernel Stream Compaction and Its Application to Multi-Kernel Data Visualization on General-Purpose GPUs. Computer Graphics Forum 32(6), 178-188.

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Teaching

  • CS-255 Computer Graphics

    This module will provide an introduction to the use of computer graphics and its applications particularly for image processing and the production of realistic representations.

Supervision

  • 'Using Tangible User-Interfaces to Aid Understanding of Cultural Heritage Artefacts in a Virtual Reality Environment' (current)

    Student name:
    MSc
    Other supervisor: Dr Gary Tam
  • Higher dimensional colour mapping and transfer functions for image and volume data (provisional) (current)

    Student name:
    PhD
    Other supervisor: Dr Xianghua Xie
  • Representation Learning in Irregular Domains. (current)

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

    Student name:
    PhD
    Other supervisor: Dr Xianghua Xie
  • Visualisation and Machine Learning. (current)

    Student name:
    PhD
    Other supervisor: Dr Xianghua Xie
  • 'Quality Assessment and Variance Reduction in Monte Carlo Rendering Algorithms«br /» ' (awarded 2018)

    Student name:
    PhD
    Other supervisor: Dr Benjamin Mora
  • 'Visual Analysis of Large, Time-Dependant, Multi-Dimensional Smart Sensor Tracking Data.' (awarded 2017)

    Student name:
    PhD
    Other supervisor: Dr Bob Laramee

Research Groups

Administrative Responsibilities

  • Director of Admissions

    2011 - 2014

  • REF Working Group

    2012 - Present

  • REF Environment Lead

    2012 - Present

External Responsibilities

  • Programme chair and co-chair of BMVC 2015, BMVC

    2015 - 2015

  • Member of the Editorial Board (Associate Editor), Computer Graphics Forum

    2014 - 2017

  • RIVIC Management Board, RIVIC

    2010 - Present

  • Organiser, RIVIC Graduate School, 2014

    2014 - 2014