Domantas Dilys

Domantas Dilys



My current research builds on the existing expertise in vortex ring analysis and visualisation, in combination with topological data analysis and scientific visualisation. Vortex rings fuel vertical cloud development, therefore my work is closely related to Meteorology, as clouds play a very important role in climate models. Understanding the world around us relies heavily on our sensory system. Scientific visualisation, combined with data analysis, can be seen as an extension of our sensory system – as it enables us to “sense” what we cannot otherwise see, hear, smell, taste or touch. This is precisely where my interest in visual, multidisciplinary work stems from.

Past Studies

My University of Leeds journey started back in 2017, having enrolled the Joint Masters Program – Computer Science with High-Performance Graphics and Games Engineering (MEng, BSc). Computer Graphics found itself as an intersection of quite a few topics I had always been interested in – from Computer Science, Physics and Mathematics, to Video Games, Art and Design.

During this course I have chosen to take up the one-year work placement, working at RAL Space with satellite data and atmospheric pollutant retrievals. Precisely during this time the career path started forming in the direction of Scientific Visualisation and Data Analysis. Yet again, the area of Computer Graphics found itself conveniently placed within these disciplines, as algorithms and data analysis techniques have to be merged with graphics techniques for efficient visualisation. After all, an interesting way to describe visualisation is to view it as the most efficient data compression technique, turning billions of numbers into images.

Current Studies

The current stage of my career began in 2022 October with the start of the PhD at University of Leeds in project “Application of Topological Data Analysis and Visualisation Techniques to Atmospheric Science”. Climate change is a pressing issue and is studied by testing mathematical descriptions of environmental phenomena against the real-life observations. High-performance computers are used to solve these mathematical equations and generate more data than can be manually inspected. Data is only useful if it can be interpreted. The aim of visualisation is to summarise the data, by extracting the important information, and displaying it. As data sizes grow, existing visualisation tools fail. The aim of my research is designing new scalable tools for inspecting large meteorological datasets, using Topological Data Analysis - for extracting the core information - and visualisation techniques – for displaying the results.

Research interests

Scientific Visualisation, Computer Graphics, Meteorology