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Dr. John Dingliana

Assistant Professor (Computer Science)


Dr. John Dingliana graduated with a B.Sc. Honors degree in Computer Science from University College Dublin in 1998 and received his PhD in the Department of Computer Science, Trinity College Dublin in 2003. His PhD thesis was titled Adaptive Levels of Detail for Interactive Collision Handling. He was appointed as a Lecturer in Computer Science from 2000-2002 and Research Fellow in the Interaction Simulation and Graphics group, TCD from 2002-2005. Since July 2005 he is an Assistant Professor in the School of Computer Science and Statistics, Trinity College Dublin. His main research interests are in real-time computer graphics, interactive visualisation and augmented and virtual reality.
  3-D MODELLING   ALGORITHMS   ANIMATION   COLLISION HANDLING   Computer Animation   Computer Graphics   Computer graphics, Meta computing   Computer Science   Computer Science/Engineering   Digital systems, representation   Interactive Visualisation   Modelling, modelling tools, 3D modelling   Non-photorealistic Animation and Rendering (NPAR)   Programming, Information systems   Real-Time Computing   Scientific Visualisation   Virtual Reality   Volume Graphics
 aRTIVVIS: Real-time Time-variant Volume Visualisation
 INFOCARVE: Focus and Context Visualisation for Augmented Reality
 The Book of Kells: Investigations of style and design through Non-photorealistic Rendering techniques
 Perceptually Optimized Rendering for Dynamic 3D Visualization
 Interactive 3D Authoring and Non-Photo-realistically Rendered Interfaces

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Details Date
Chair of the Irish Chapter of the European Association for Computer Graphics (EUROGRAPHICS) May 2014
Reviewer - IEEE Transactions on Visualization and Computer Graphics Journal
Reviewer - Computer Graphics Forum Journal
Reviewer - ACM Transactions on Applied Perception Journal
Reviewer - International Journal of Systems & Applications in Computer Graphics
Reviewer for International Journal of Interactive Worlds
Reviewer - Electronics and Telecommunications Research Institute (ETRI) Journal
Reviewer - Frontiers of Information Technology & Electronic Engineering Journal
Reviewer IEEE Spectrum magazine
Reviewer - ACM SIGGRAPH Asia Courses
Co-chair VRIPhys 2007: International Workshop on Virtual Reality Interactions and Physical Simulations 2007
Reviewer - ACM Siggraph
Co-chair: EUROGRAPHICS 2005 Short Paper programme 2005
Programme Co-chair - Eurographics Ireland Workshop March 2002
Language Skill Reading Skill Writing Skill Speaking
English Fluent Fluent Fluent
German Basic Basic Basic
Hindi Basic Basic Basic
Details Date From Date To
EUROGRAPHICS: European Association for Computer Graphics 1999 2019
Association for Computing Machinery (ACM) - SIGGRAPH Member 2001 2019
IEEE Visualization and Graphics Technical Committee 2014 2019
Subhrajyoti Maji and John Dingliana, Perceptually Optimized Color Maps for Visualizing Large Numbers of Features, Second International Conference on Advanced Computational and Communication Paradigms, Sikkim Manipal Institute of Technology, Sikkim, India, February 25 - 28, IEEE, 2019, Conference Paper, ACCEPTED
Salaheddin Alakkari and John Dingliana, An Accelerated Online PCA with O(1) Complexity for Learning Molecular Dynamics Data, Workshop on Molecular Graphics and Visual Analysis of Molecular Data, Brno, Czech Republic, June 4, 2018, 2018, pp1-8 , Conference Paper, PUBLISHED
Shengzhou Luo and John Dingliana, Intuitive Transfer Function Editing Using Relative Visibility Histograms, 26, (1), 2018, p48-57 , Journal Article, PUBLISHED  TARA - Full Text
Salaheddin Alakkari, A Multi-View Image-Based Volume Visualization Technique, IEEE Visualization, Berlin, Germany, October 21 -- 26, 2018, Poster, PUBLISHED  TARA - Full Text
Subhrajyoti Maji and John Dingliana, A Perceptually Optimized Color Selection Technique for Visualization , IEEE Visualization, Berlin, Germany, October 21 -- 26, 2018, Poster, PUBLISHED  TARA - Full Text
Principal Component Analysis Techniques for Visualization of Volumetric Data in, editor(s)Ganesh Naik , Advances in Principal Component Analysis - Research and Development, Springer Verlag, 2017, pp99 - 120 , [Salaheddin Alakkari and John Dingliana], Book Chapter, PUBLISHED  DOI
Shengzhou Luo and John Dingliana, Transfer function optimization using a combined measure of visibility and saliency, Spring Conference on Computer Graphics, Mikulov, Czech Republic, May 15 - 17, 2017, 2017, Conference Paper, PUBLISHED  DOI
Lazaro Campoalegre, Tom Noonan and John Dingliana, Exploiting Spatio-temporal Coherency in Time-Varying Visualization Over Network Environments, Computer Graphics, Visualization, Computer Vision and Image Processing, Lisbon, Portugal, 21 July, 2017, edited by Yingcai Xiao and Ajith P. Abraham , 2017, pp163 - 172, Conference Paper, PUBLISHED
Ran, L. and Dingliana, J., Infocarve: A Framework for Volume Visualization on Commodity Augmented Reality Displays, (7938241), 2017, pp473-479 , Notes: [cited By 0], Conference Paper, PUBLISHED  DOI
Shengzhou Luo and John Dingliana, Intuitive Transfer Function Editing Using Relative Visibility Histograms, IEEE Vis, Phoenix, Arizona, USA, 1 - 6 October, 2017, Poster, PRESENTED
  

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John Dingliana, Expressive Volume Visualisation, Invited Seminar at Universitat Polytecnica de Catalunya, VIRVIG Group, UPC, Barcelona, Spain, 22 April, 2015, Invited Talk, PRESENTED
Sayandeep Purkayasth, A Hierarchical Image Processing Approach to Analysis of Early Medieval Manuscript Art, 2015, Thesis, PUBLISHED
John Dingliana, Architecture in Virtual Environments, LunchBytes series Panel on Society: Public Space/Architecture, Irish Museum of Modern Art, Kilmainham, Dublin, 17 October, 2014, Goethe Institute and Irish Museum of Modern Art, Invited Talk, PRESENTED
John Dingliana, The History of Video Games Technology, Cork Film Festival, Cork, Ireland, 14th October, 2008, Invited Talk, PRESENTED

  

Award Date
Günter Enderle Award for Best Paper at Eurographics Annual Conference 2010 7 May, 2010
Best Paper Award - International Conference on Computer Graphics, Visualization , Computer Vision and Image Processing (CGCVIP) July 2017
Best Poster Award - Eurographics / IEEE-VGTC Conference on Visualization (EuroVis) June, 2016
My research lies in the fields of Computer Graphics and Visualization, specifically areas including animation, rendering, perceptually-adaptive techniques, visualization, stylised images and Augmented & Virtual Reality. The consistent thread in my research is the question of how information is optimally conveyed through visual digital media, in the context of increasing complexity of data, evolving display technologies and their widening uptake in user domains beyond those traditionally associated with computer graphics. Recent technological advances have vastly increased the scale of digital data that we process on an everyday basis, while graphics technology has reached levels fidelity that match perceptual limits of the human visual system. This raises many new challenges but also opportunities for furthering human consumption of data and enriching visual applications. I investigate how the most important aspects of static, dynamic and interactive data can be emphasized to help users process visual information, and how to simplify where detail is not warranted. Visual output is thereby optimized for tasks ranging from leisurely goals such as enjoyment, engagement or aesthetics to precision-oriented objectives such as visual analysis in science and medicine. My early publications were amongst the first to apply adaptive detail mechanisms in Physically-based animation and to leverage human perceptual studies of movement to optimize this adaptation. In more recent, work I conducted analogous studies applying perceptually-driven adaptation to other areas such as rendering and ultimately to solve real-world scientific problems such as real-time visualization of time-varying data, for which I received an SFI Investigator award. A key outputs of this project was one for the first models to provide automated measures for perceptual effectiveness of 3D spatial data visualization, and to use this model to automatically enhance such visualizations.