Computer Vision

Karen Sanchez

Postdoctoral Research Fellow

Computer Vision machine learning AI for healthcare deep learning Medical imaging

Karen Sanchez is a Postdoctoral Researcher in the IVUL lab at KAUST, specializing in deep learning, machine learning, and artificial intelligence (AI) for healthcare applications. Her research focuses on video understanding, domain adaptation, generative AI, and methods for preserving patient privacy.

Aznaur Aliev

M.S. Student

AI Deep learning Computer Vision Reinforcement Learning

Hani A. Al Majed

M.S. Student

machine learning Computer Vision AI4Science

Electrical and Computer Engineering Master's student at KAUST under the supervision of Professor Bernard Ghanem, with expertise in machine learning workflow automation, physics-informed neural operators, and AI for Science, particularly in chemistry applications. Passionate about leveraging AI to solve complex scientific problems.

Ahmad Sait

M.S. Student, Computer Science

Computer Vision machine learning Deep generative models

Ahmad Sait is a Master's student in the Computer Science program at KAUST. Before joining KAUST, Ahmad obtained his Bachelor's degree in Computer Science from King Abdulaziz University, Saudi Arabia. Ahmad is also a KAUST Academy graduate from the AI track, having been under the supervision of Prof. Naeemullah Khan. The Academy provided him with seven opportunities to assist in teaching students enrolled in subsequent cohorts.

Ganesh Sundaramoorthi

Assistant Professor, Electrical and Computer Engineering

Computer Vision optimization geometric modeling

Ganesh Sundaramoorthi was an Assistant Professor of Electrical Engineering and jointly Assistant Professor of Applied Mathematics and Computational Science at KAUST starting in 2011. He is currently Principal Research Scientist at United Technologies Research Center in East Hartford, CT, USA, formulating computer vision algorithms for robotic inspection applications. Education and Early Career His PhD is in Electrical and Computer Engineering from the Georgia Institute of Technology in Atlanta, GA, USA in 2008. His PhD developed fundamental shape optimization methods for computer vision that