Dr Bob Laramee
Associate Professor
Computer Science
Telephone: (01792) 602609
Email: JavaScript is required to view this email address.
Room: Office - 113
First Floor
Computational Foundry
Bay Campus

Areas of Expertise

  • data visualization
  • flow visualization
  • information visualization
  • visual analytics
  • big data visualization

Publications

  1. & (2018). Dynamic Choropleth Maps – Using Amalgamation to Increase Area Perceivability. Presented at 2018 22nd International Conference Information Visualisation (IV),, 284-293. Fisciano, Italy: doi:10.1109/iV.2018.00056
  2. & A Survey of Information Visualization Books. Computer Graphics Forum
  3. & Visualization for Smart City Applications. IEEE Computer Graphics and Applications 38(5), 36-37.
  4. & Feature Surfaces in Symmetric Tensor Fields Based on Eigenvalue Manifold. IEEE Transactions on Visualization and Computer Graphics 22(3), 1248-1260.
  5. & Smart Brushing for Parallel Coordinates. IEEE Transactions on Visualization and Computer Graphics, 1-1.

See more...

Teaching

  • CSC009 Technologies for Information Presentation

    This module is about the technologies and markup languages that make various forms of data presentation possible. It will explore web-based presentation languages including HTML, XML and CSS, text presentation languages including LaTeX, and mathematical / graphical presentation through R. After studying this module, students will be able to build web sites, produce professional-quality reports and typeset and visualize mathematical formulae and data, using the appropriate graphs for the data. The students will also be able to produce a crawler / scraper that can pull data from websites automatically for analysis.

  • CSC337 Data Visualisation

    Data Visualization is concerned with the automatic or semi-automatic generation of digital images that depict data in a meaningful way(s). It is a relatively new field of computer science that is rapidly evolving and expanding. It is also very application oriented, i.e., real tools are built in order to help scientists from other disciplines.

  • CSCM37 Data Visualization

    Data Visualization is concerned with the automatic or semi-automatic generation of digital images that depict data in a meaningful way(s). It is a relatively new field of computer science that is rapidly evolving and expanding. It is also very application oriented, i.e., real tools are built in order to help scientists from other disciplines.

Supervision

  • Untitled (current)

    Student name:
    PhD
    Other supervisor: Dr Sean Walton
  • Dynamic Geospatial Visualization (current)

    Student name:
    PhD
    Other supervisor: Prof Markus Roggenbach
  • Interactive Visualization of Molecular Dynamics Simulation Data (current)

    Student name:
    PhD
    Other supervisor: Dr Adeline Paiement
  • Metaphors for Molecules: Alternative Graphical Representations for Molecular Dynamic Simulation Data«br /»«br /»«br /» (current)

    Student name:
    MSc
    Other supervisor: Dr Adeline Paiement
  • Visual Analysis of Translation Data (current)

    Student name:
    PhD
    Other supervisor: Dr Adeline Paiement
  • Interactive Visual Analysis Techniques for Call Centre Data (current)

    Student name:
    PhD
    Other supervisor: Dr Deepak Sahoo
  • Interactive Visualisation of Engineering Applications (current)

    Student name:
    PhD
    Other supervisor: Prof Andrew Barron
  • Design, compilation and applications of an English-Polish-Belarusian Parallel Literary Corpus (current)

    Student name:
    PhD
    Other supervisor: Prof Tom Cheesman
  • Computer vision based analysis of multi-modal images of the Martian surface (current)

    Student name:
    PhD
    Other supervisor: Prof Xianghua Xie
  • Advanced Visualization for Education (current)

    Student name:
    PhD
    Other supervisor: Dr Mabrouka Abuhmida
  • Visualising the customer journey through the Call-Center landscape (awarded 2019)

    Student name:
    PhD
    Other supervisor: Dr Sean Walton
  • Geo-spatial Visualization of Public Health Care Data (awarded 2019)

    Student name:
    PhD
    Other supervisor: Dr Daniel Archambault
  • 'Topological visualisation techniques to enhance understanding of Lattice QCD simulations«br /» ' (awarded 2018)

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

    Student name:
    PhD
    Other supervisor: Prof Mark Jones