Profiles

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.

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.

Peter started his academic life at Vienna University of Technology (TU Wien). He obtained his bachelor degree in Media Computer Science in 2003. After that, he worked as a teacher assistant for one year. In 2005, he received his master degree in Computer Graphics and Digital Image Processing. During his preparation for the master degree, he worked part-time as a Computer Science teacher at a School for Social Services.

He was a Research Assistant from 2005 to 2009 at TU Wien. In that period, he was also preparing doing his PhD in Computer Science. He received his doctoral degree in 2009. Before joining KAUST, Peter was a Postdoctoral Fellow at the Vienna University of Technology until 2011.

Peter is interested in Scientific Visualization, particularly in advanced methods of fluid flow visualization, Computer Graphics in general, Augmented and Virtual Reality, as well as large language models (LLMs) and their applications in interactive systems.

Xingdi Zhang holds a Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST), where he was advised by Professor Markus Hadwiger in the High-Performance Visualization Group. He received her M.S. in Computer Science from KAUST in 2022 and  B.E. from the Yingcai Honor College at the University of Electronic Science and Technology of China (UESTC) in 2020. His research bridges scientific visualization, computer graphics, differential geometry, and calculus of variations, with a focus on optimal reference frames in unsteady flow, Lagrangian vortex corelines, and observer-relative flow visualization.

• Scientific Visualization & Computer Graphics: Observer-relative vortex extraction, optimal reference frames, Lagrangian vortex corelines, discrete geometry, and graphics engines.
• Mathematics: Differential Geometry, Calculus of Variations.
• AI4science: learning-based flow feature extraction

Amani Ageeli is a Ph.D. candidate in Computer Science at King Abdullah University of Science and Technology (KAUST), working in Prof. Markus Hadwiger research group High-Performance Visualization Group. She earned her master’s degree in Computer Science from KAUST and her bachelor’s degree in Computer Science from Umm Al-Qura University. Her doctoral research focuses on developing compact, efficient approaches for analyzing large-scale, time-dependent scientific data. Throughout her studies, she has contributed to teaching and supporting visualization and programming courses, and has also taught pre-university students through KAUST educational programs such as KVA and Space2101.

Amani is passionate about computer graphics, scientific visualization, real-time rendering, and virtual and augmented reality. Aside from research, Amani enjoys teaching, she joined as a TA in couple of graduate courses and for high school student program. Amani has experience in design and technical illustration, with interests spanning GPU-based visualization, real-time rendering, scientific visualization, and scientific illustration.

Xingdi Zhang holds a Ph.D. in Computer Science from King Abdullah University of Science and Technology (KAUST), where he was advised by Professor Markus Hadwiger in the High-Performance Visualization Group. He received her M.S. in Computer Science from KAUST in 2022 and  B.E. from the Yingcai Honor College at the University of Electronic Science and Technology of China (UESTC) in 2020. His research bridges scientific visualization, computer graphics, differential geometry, and calculus of variations, with a focus on optimal reference frames in unsteady flow, Lagrangian vortex corelines, and observer-relative flow visualization.

• Scientific Visualization & Computer Graphics: Observer-relative vortex extraction, optimal reference frames, Lagrangian vortex corelines, discrete geometry, and graphics engines.
• Mathematics: Differential Geometry, Calculus of Variations.
• AI4science: learning-based flow feature extraction

Dr. Sicat obtained his bachelor degree in Electronics and Communications Engineering from Ateneo de Manila University in Philippines in 2008. After graduating, he worked as a Research Assistant and Lecturer for almost a year before joining KAUST to receive his master degree in Electrical Engineering and his Ph.D. in Computer Science.

Afterward, he worked as a Postdoctoral Fellow at Visual Computing Center (VCC) in KAUST. He left KAUST to join Harvard University as a Postdoctoral Researcher, until he returned to KAUST in 2019 as a Research Scientist to continue his research journey.

His main research interests are large-scale data visualization and analysis, immersive analytics, and computer graphics. He develops multi-resolution representations and algorithms for large-scale gigapixel images, and 3D volumes. He also develops visualization tools and techniques for augmented and virtual reality environments towards novel ways of experiencing and understanding data.