Thesis supervisor: Ildikó Papp
Location of studies (in Hungarian): University of Debrecen Faculty of Informatics Abbreviation of location of studies: DE IK
Description of the research topic:
Syllabus
Information visualization has arguably been the fastest-growing branch of the visualization discipline for the last decade. Its rapid and sustained growth is apparent both in the various industry branches that make use of infovis applications (ranging from banking and telecom to information technology) and in the logistics and administrative departments of large companies. In all of these cases, the challenge is the same: the various activities performed by the respective industry generate a huge amount of data. Data visualization is an extensive field at the crossroads of mathematics, computer science, cognitive and perception science, and engineering. A prominent aspect of scientific visualization is the depiction of datasets that have a natural spatial embedding, i.e., datasets whose elements or data points have positions with particular significance in space.
Scientific visualization, or scivis for short, can be described as being “primarily concerned with the visualization of three-dimensional phenomena (architectural, meteorological, medical, biological, etc.), where the emphasis is on realistic renderings of volumes, surfaces, illumination sources, and so forth, perhaps with a dynamic (time) component”
The computation, generalization and application of these surfaces types to specified problems are in the focus of this subject.
Bibliography
[1] Alexandru C. Telea: Data Visualization: Principles and Practice, Second Edition, A K Peters/CRC Press, 2014.
[2] Gerald Farin, Dianne Hansford: Mathematical Principles for Scientific Computing and Visualization, A K Peters/CRC Press, 2008.
[3] Helen Wright: Introduction to Scientific Visualization, Springer, 2007.
[4] Colin Ware: Information Visualization, Third Edition: Perception for Design (Interactive Technologies), Morgan Kaufmann, 2012.
[5] Matthew O. Ward, Georges Grinstein, Daniel Keim: Interactive Data Visualization, Foundation, Techniques, and Applications, A K Peters/CRC Press, 2010.
Deadline for application: 2022-11-15
2024. IV. 17. ODT ülés Az ODT következő ülésére 2024. június 14-én, pénteken 10.00 órakor kerül sor a Semmelweis Egyetem Szenátusi termében (Bp. Üllői út 26. I. emelet).
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