scientific computing

Observer-Relative Flow Visualization and Objective Feature Extraction

Xingdi Zhang, Ph.D. Student, Computer Science

Nov 19, 16:30 - 18:00

B1 L4 R4214

visual computing scientific computing deep learning

This dissertation develops an integrated toolkit of novel visualization and feature extraction methods, grounded in a Riemannian geometry framework, to enable an objective, observer-relative, and physically consistent analysis of complex unsteady flows.

Georgios Grekas

Georgios Grekas

Postdoctoral Research Fellow, Applied Mathematics and Computational Science

solid mechanics biomechanics numerical analysis scientific computing

Haneen Mohammed

M.S., Computer Science

Scientific Visualization computer networks scientific computing

Haneen Mohammed was a Master student in Computer Science Program under the supervision of Professor Markus Hadwiger at Visual Computing Center (VCC) at King Abdullah university of Science and Technology (KAUST). Currently, she’s preparing her doctoral in Computer Science at Columbia University in the City of New York, United States. Education and Career Haneen earned her bachelor degree in Electrical and Computer Engineering from Effat University in Jeddah in 2015. She joined KAUST and received her master degree in Computer Science in 2017. Research Interest Her research interests are mainly