The fifth annual international summit ‘Machines Can See’ will host IVUL's own Prof. Bernard Ghanem as a speaker. The summit, to be held on July 8th 2021, is hosted by VisionLabs, a leading software company devoted to developing products based on state-of-the-art Computer Vision algorithms.

The 2021 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) has granted Outstanding Reviewer awards to seven members of IVUL: Alejandro Pardo, Ali Thabet, Chen Zhao, Mattia Soldan, Mengmeng Xu, Juan C. Pérez, and Silvio Giancola.

Juan C. Pérez is a biomedical engineering graduate from Universidad de Los Andes, Colombia, who joined KAUST in January 2021. Juan first came to KAUST as an intern and was amazed by its excellent research atmosphere, environment, and resources. These factors served as an impetus in choosing KAUST as the destination to further his academic career.

The 2020 European Conference on Computer Vision (ECCV 2020) is the top European conference in the image analysis area. One of their workshops aims to bring together researches from the fields of adversarial machine learning, robust vision and explainable AI to discuss recent research and future directions for adversarial robustness and explainability, with a particular focus on re

Sara Rojas Martínez is a 24-year-old Biomedical Engineering graduate from Bogotá, Colombia. Since childhood, Sara was fascinated by robots, technology, and artificial intelligence (AI). Her interest in technology motivated her to pursue a bachelor's degree in electrical engineering. After obtaining her bachelor's degree from Universidad de los Andes, Bogotá, she realized that she wanted to do something related to AI and humans, so she also pursued her master’s degree from the same university.

Teaching has the power to test the limits of one's knowledge. Teaching algorithms to learn using machine learning is making it possible for cars to do away with human drivers in the near future, but this has also opened up new questions about the limits of our knowledge of the brain and learning.