Dr. John Dingliana

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

My research focuses on Computer Graphics and Visualization, and specialised areas of 3D modelling, animation, rendering, perception and Augmented & Virtual Reality. The central theme in my work is exploring how information is most effectively conveyed through visual digital media, particularly as data complexity increases, display technologies evolve, and these tools become more widely used in fields beyond traditional computer science. My work aspires towards making advanced computer visualisation techniques to interdisciplinary users, and to this end I have collaborated with partners from diverse disciplines include creative arts, psychology, culture heritage, medicine and news media. Recent technological advances have significantly expanded the scale of digital data we process daily, while the fidelity of sensor and display technologies now surpasses the perceptual limits of the human visual system. This presents both challenges and opportunities for research on enriching visual applications to enhance human consumption of data. My work explores how key aspects of static, dynamic, and interactive data can be emphasized to improve human understanding of visual information, enhancing critical details or simplifying where necessary. This optimization serves leisure applications from computer games and digital creativity, to precision-oriented goals, such as scientific and medical analysis. My early PhD and postdoctoral research was amongst the first to apply adaptive detail strategies that use human motion perception to optimise computer generated animations. Later, as PI, I extended this approach to optimizing computer images in general, addressing real-world problems such as the visualization of complex time-varying scientific data, which was integral to my three SFI-funded projects as PI and in my contributions to the Prendergast Challenge award, Life in the Currents. In later years, I further applied these methodologies to nascent areas of research including Augmented Reality and AI-driven techniques for visualisation, featured in my work on the EU-FP7 VERVE and Horizon-EU TRANSMIXR projects.