Markus Hadwiger

Professor, Computer Science
Principal Investigator, High Performance Visualization Group

markus.hadwiger@kaust.edu.sa

Markus Hadwiger is a Professor of Computer Science at the King Abdullah University of Science and Technology (KAUST). A founding member of the University, he conducts fundamental and applied research in scientific visualization and visual computing.

Biography

A founding member of KAUST, Hadwiger has published numerous scientific papers and books, including "Real-Time Volume Graphics." He has been an Assistant Professor of Computer Science from 2009 to 2014, an Associate Professor of Computer Science from 2014 to 2021, and a Full Professor of Computer Science since 2021.

Research Interests

Professor Markus Hadwiger’s research interests are in scientific visualization and visual computing.

Hadwiger’s investigations span a wide range of topics, including the visualization of extreme-scale data, volume visualization, flow visualization, differential geometry and mathematical physics in visualization, medical visualization, large-scale image and volume processing, multi-resolution and out-of-core techniques, domain-specific languages for visualization, interactive segmentation and feature identification and GPU algorithms and architecture.

Awards and Distinctions

Honorable Mention for Best Paper Award (top four papers), IEEE Information Visualization, 2014
Best Poster Award, Symposium on Biological Data Visualization (BioVis 2014), 2014
Honorable Mention for Best Paper Award (top five papers), IEEE Pacific Visualization 2013, 2013
Honorable Mention for Best Paper Award (top three papers), IEEE Scientific Visualization 2012, 2012
Best Application Paper Award, IEEE Visualization 2007, 2007

Education

Doctor of Philosophy (Ph.D.): Computer Science, Vienna University of Technology, Austria, 2004

Diploma (Dipl.-Ing.-M.Eng.): Computer Science, Vienna University of Technology, Austria, 2000

Questions and Answers

Why KAUST?

The unique vision and interdisciplinarity of KAUST make it the most exciting place for research on visually understanding massive data, whether from neuroscience, materials science, computational fluid dynamics, mathematical physics, neural networks, or other areas. My research is in visualization, and few have said it as well as John Tukey: "The greatest value of a picture is when it forces us to notice what we never expected to see." (Exploratory Data Analysis, 1977).

Why visual computing?

Visual computing is a dynamic and diverse research field that thrives on its interdisciplinary nature, fostering collaborations with researchers and engineers across a wide array of scientific and engineering disciplines. This cross-disciplinary engagement continually drives innovation and keeps our research both engaging and cutting-edge. The field is particularly rewarding because it provides immediate visual feedback, offering a more intuitive understanding of data compared to purely numerical analysis.