Computer Vision

Deep learning accelerates research on early pregnancies

1 min read ·
KAUST researchers have created deepBlastoid, a deep learning tool that surpasses scientists at evaluating laboratory models of the human embryo before pregnancy

Adonai Vera

Machine Learning Engineer with 6+ years of experience specializing in computer vision, deep learning, and robotics. Led AI solutions for retail analytics, UAV systems, and edge devices. Author, educator, and TensorFlow Google Developer Expert.

Abdelrahman Eldesokey

Postdoctoral Research Fellow
I am a Postdoctoral Fellow at KAUST, Saudi Arabia, specializing in Generative AI and conducting research on advanced topics in Generative and Large Language Models (LLMs). I bring over 11 years of combined academic and industrial experience in Computer Vision and Deep Learning across Sweden, Egypt, and Saudi Arabia.
Najmeddine Dhieb

Najmeddine Dhieb

Karen Sanchez

Postdoctoral Research Fellow
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

Hani A. Al Majed

M.S. Student
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
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.

Sim-to-Real Transfer for Autonomous Navigation

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B2 L5 R5220

This work investigates the problem of transfer from simulation to the real world in the context of autonomous navigation. To this end, we first present a photo-realistic training and evaluation simulator Sim4CV which enables several applications across various fields of computer vision. Built on top of the Unreal Engine, the simulator features cars and unmanned aerial vehicles (UAVs) with a realistic physics simulation and diverse urban and suburban 3D environments. We demonstrate the versatility of the simulator with two case studies: autonomous UAV-based tracking of moving objects and autonomous driving using supervised learning.

Efficient Localization of Human Actions and Moments in Videos

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B3 L5 R5220

Abstract We are stumbling across a video tsunami flooding our communication channels. The ubiquity of digital cameras and social networks has increased the amount of visual media content generated and shared by people, in particular videos. Cisco reports that 82% of the internet traffic would be in the form of videos by 2022. The computer vision community has embraced this challenge by offering the first building blocks to translate the visual data in segmented video clips into semantic tags. However, users usually require to go beyond tagging at the video level. For example, someone may want

An Egocentric Computer Vision-based Robotic Wheelchair

Mohammed Kutbi, Assistant Professor at the department of Computer Science and a member of the Artificial Intelligence Unit at Saudi Electronic University (SEU)

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B3 L5 R5209

The emerging need to improve the quality of life for elderly and disabled individuals who rely on wheelchairs for mobility is our motivation for this work. Research on robotics wheelchair covers broad range from motion control, how to control the wheelchair movement, to complete autonomy.

Understanding a Block of Layers in Deep Neural Networks: Optimization, Probabilistic and Tropical Geometric Perspectives

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KAUST

In this dissertation, we aim at theoretically studying and analyzing deep learning models. Since deep models substantially vary in their shapes and sizes, in this dissertation, we restrict our work to a single fundamental block of layers that is common in almost all architectures. The block of layers of interest is the composition of an affine layer followed by a nonlinear activation function and then lastly followed by another affine layer. We study this block of layers from three different perspectives. (i) An Optimization Perspective. We try addressing the following question: Is it possible that the output of the forward pass through the block of layers highlighted above is an optimal solution to a certain convex optimization problem? As a result, we show an equivalency between the forward pass through this block of layers and a single iteration of certain types of deterministic and stochastic algorithms solving a particular class of tensor formulated convex optimization problems.

Indoor 3D Scene Understanding Using Depth Sensors

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KAUST

One of the main goals in computer vision is to achieve a human-like understanding of images. This understanding has been recently represented in various forms, including image classification, object detection, semantic segmentation, among many others. Nevertheless, image understanding has been mainly studied in the 2D image frame, so more information is needed to relate them to the 3D world. With the emergence of 3D sensors (e.g. the Microsoft Kinect), which provide depth along with color information, the task of propagating 2D knowledge into 3D becomes more attainable and enables interaction between a machine (e.g. robot) and its environment. This dissertation focuses on three aspects of indoor 3D scene understanding: (1) 2D-driven 3D object detection for single frame scenes with inherent 2D information, (2) 3D object instance segmentation for 3D reconstructed scenes, and (3) using room and floor orientation for automatic labeling of indoor scenes that could be used for self-supervised object segmentation. These methods allow capturing of physical extents of 3D objects, such as their sizes and actual locations within a scene.

Stylistic and spatial disentanglement in GANs

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KAUST

This dissertation tackles the problem of entanglement in Generative Adversarial Networks (GANs). The key insight is that disentanglement in GANs can be improved by differentiating between the content, and the operations performed on that content. For example, the identity of a generated face can be thought of as the content, while the lighting conditions can be thought of as the operations.

Rising Stars in AI Symposium 2022 at KAUST

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B4 B5 A0215

Rising Stars in AI Symposium 2022 at KAUST The "Rising Stars in AI Symposium" is geared towards young researchers (including PhD students, PostDocs, young faculty) who have recently published promising work at leading venues. There will be dozens of brief in-person presentations about papers recently accepted at major AI conferences such as NeurIPS, CVPR, EMNLP, ACL, ICML, ICLR, etc. All speakers will be encouraged to start with an intro for non-AI experts. To view the complete program and for more event details, please visit the symposium website. Attend the Symposium The symposium will be

Omics-based Metastasis Prediction using Machine Learning and Deep Learning

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KAUST

Knowing metastasis is the primary cause of cancer-related deaths incentivized research to unravel the complex cellular processes that drive the metastasis. Advancement in technology and specifically the advent of high-throughput sequencing provides knowledge of such processes. This knowledge led to the development of therapeutic and clinical applications. In this regard, predicting metastasis onset has also been explored using artificial intelligence (AI) approaches that are machine learning (ML), and more recently, deep learning (DL).

Towards Detailed Understanding of the Visual World

Fahad Khan, Associate Professor at MBZUAI and Linköping University

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B9 L2 R2322

Machine perception that corresponds to the ability to understand the visual world based on the input from sensors, such as cameras is one of the central problems in Artificial Intelligence. To this end, recent years have witnessed tremendous progress in various instance-level recognition tasks having real-world applications in e.g., robotics, autonomous driving and surveillance. In this talk, I will first present our recent results towards understanding state-of-the-art deep learning-based visual recognition networks in terms of their robustness and generalizability. Next, I will present our results on learning visual recognition models with limited human supervision. Finally, I will discuss moving one step further from instance-level recognition to understand visual relationships between object pairs.

Bridging the Gap between the Academia and Industry by Extending High-Quality Research to Practical Business Needs

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B9 L2 R2322 H1

This seminar focuses on providing the audience with the context and scope of our internship program. The program is for the young and talented graduate students with an active interest in solving real-world problems. Some of the projects that will be presented in the seminar are actively developed in Elm and include domains such as computer vision, robotics and automation, healthcare, IoT, video analytics, and NLP. The seminar will serve as a launch pad to allow students to discuss their future interests and aspirations with the speaker. It will also enable them to develop a better awareness of domains more relevant to their future research aspirations.

Towards Richer Video Representation for Action Understanding

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B2 L5 R5209

With video data dominating the internet traffic, it is crucial to develop automated models that can analyze and understand what humans do in videos. Such models must solve tasks such as action classification, temporal activity localization, spatiotemporal action detection, and video captioning. This dissertation aims to identify the challenges hindering the progress in human action understanding and propose novel solutions to overcome these challenges.

Best Business Plan at VIEW 2016

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Hachid won the award for the Venture pitch with the best business plan at the Fifth Annual Vision Industry and Entrepreneur Workshop (VIEW) 2016.

Fabian and Victor participate in the annual MSR Summer School!

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Two IVUL Ph.D. students (Fabian Caba and Victor Escorcia) participate in the annual MSR Summer School.

Adel Bibi and Matthias Mueller going to ICVSS 2017

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Adel Bibi and Matthias Mueller have been accepted to participate in the ICVSS (International Computer Vision Summer Schoole) 2017 in Italy. Admission into this summer school is quite competitive in the vision community.​​​

CEMSE New Faculty: Mohamed Elhoseiny, Assistant Professor of Computer Science

1 min read ·
Prior to joining the KAUST CEMSE Division earlier this year, Mohamed Elhoseiny received his Ph.D. degree from Rutgers University, New Brunswick in 2016, before spending over two years working as a postdoctoral researcher at Facebook in the company’s AI research wing. Elhoseiny joins the Division as an assistant professor of computer science based in the KAUST Visual Computing Center (VCC). He will also act as the PI of the KAUST Computer Vision, Content AI (Vision-CAIR) Research Group. Outside of his duties at KAUST, he is also acting as an artificial intelligence (AI) research consultant for Baidu Research, Silicon Valley AI Lab.

KAUST Ph.D. student Jinhui Xiong wins best paper award

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KAUST computer science Ph.D. student Jinhui Xiong recently won the best paper award at the 24th International Symposium on Vision, Modeling, and Visualization. The symposium took place from September 30 to October 2, 2019, at the University of Rostock, Germany, and provided the opportunity for researchers to discuss a wide range of topics in computer science, including computer graphics, vision, visualization and visual analytics.

Meet KAUST prospective student: Matheus Vinícius Medeiros de Souza

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Matheus Vinícius Medeiros de Souza is a 24-year-old electrical engineering graduate from the city of Natal, Brazil. Matheus first came to KAUST as a visiting student in 2019 and was instantly impressed by the university’s research facilities.

Meet KAUST Prospective Student: Xinge Yang

1 min read ·
Xinge Yang is a 22-year-old graduate who will join KAUST from the University of Science and Technology of China (USTC). Yang will join the University in the fall of 2020 as an M.S./Ph.D. candidate in the KAUST Computational Imaging Group under the supervision of Professor Wolfgang Heidrich.

KAUST prospective student: Qizhou Wang

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Qizhou Wang, 22, is a communication engineering graduate who will join KAUST from the University of Electronic Science and Technology, China. Wang will join KAUST in the fall of 2020 as a M.S./Ph.D. candidate in the KAUST Primalight Lab under the supervision of Professor Andrea Fratalocchi.

KAUST-Stanford neural network paper accepted for presentation at ECCV 2020

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A novel KAUST-Stanford University research paper by Panos Achlioptas (Stanford), Ahmed Abdelreheem (KAUST), Fei Xia (Stanford), Mohamed Elhoseiny (KAUST) and Leonidas Guibas (Stanford) was accepted for presentation at the 16th European Conference on Computer Vision (ECCV 2020).

KAUST prospective student: Xingdi Zhang

1 min read ·
Xingdi Zhang is a computer science graduate from the University of Electronic Science and Technology of China (UESTC), China. Xingdi will join KAUST in the fall of 2020 as a M.S./Ph.D. candidate and member of the KAUST High-Performance Visualization Group under the supervision of Professor Markus Hadwiger.

Meet KAUST prospective student: Kilichbek Haydarov

1 min read ·
Kilichbek Haydarov is a graduate student who will join KAUST from Uzbekistan. He will join KAUST as a M.S./Ph.D. candidate and member of the KAUST Computer Vision, Content AI research group under the supervision of Professor Mohamed Elhoseiny. Kilichbek obtained his bachelor's degree in computer science and engineering from Sejong University, South Korea.

Meet KAUST prospective student: Kai Yi

1 min read ·
Kai Yi is a graduate from Xi'an Jiaotong University (XJTU), China, who will join KAUST in the fall of 2020. Kai will join KAUST as a M.S./Ph.D. candidate and member of the KAUST Computer Vision, Content AI research group under the supervision of Professor Mohamed Elhoseiny. KAUST's high reputation and Kai's interest in computer vision and machine learning prompted him to choose the University to further his academic career.

Seven IVUL members recognized as Outstanding Reviewers by CVPR 2021

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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. CVPR, a premier annual computer vision event that will take place virtually from June 19th to June 25th, is the largest computer vision conference in the world, gathering researchers from academia and industry alike. The peer-review process through which the conference determines acceptance of papers relies on expert reviewers from across the world

Perovskites used to make efficient artificial retina

1 min read ·
KAUST researchers have built an artificial electronic retina that mimics the behaviour of the eye’s rod retina cells. Their artificial retina can recognise handwritten numbers.

Yuanhao Wang

Yuanhao Wang is a Ph. D. candidate in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Yuanhao Wang obtained his bachelor's degree in Communication Engineering from Beijing University of Posts and Telecommunications in China in 2013. In 2016, he received his master's degree in Integrated Circuits Engineering from Tsinghua University in China. Research Interest Yuanhao’s research interests encompass a wide range of topics in computational photography

Yipeng Qin

Postdoctoral Research Fellow, Computer Science
Yipeng Qin was a Postdoctoral Research Fellow working with Professor Peter Wonka at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Currently, he is a Lecturer at the School of Computer Science and Informatics in Cardiff University (CU), United Kingdom. Education and Early Career In 2013, Yipeng Qin graduated with a Bachelor of Engineering in Electronic Engineering from Shanghai Jiao Tong University in China. Later during 2017, he obtained his Ph.D. in Computer Science from the National Centre for Computer Animation, Bournemouth University in

Yidan Zheng

Ph.D. Student, Computer Science
Yidan is a MS/PhD student in Computer Science at King Abdullah University of Science and Technology since August 2022, under the supervision of Prof. Wolfgang Heidrich in Computational Imaging Group. Education and Early Career Yidan obtained her bachelor’s degree in Measurement and Control Technology and Instrument from University of Science and Technology of China in 2020. Research Interest Yidan is interested in developing novel computational imaging systems in both hardware and software.

Yazeed Alharbi

Yazeed Alharbi is a Ph.D. candidate under the supervision of Prof. Peter Wonka at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career In 2015, Yazeed obtained his bachelor degree from Purdue University in the computer graphics and visualization track, with a minor in philosophy. In 2018, he received his master degree from King Abdullah University of Science and Technology (KAUST). He mainly learned about computer vision and the process of publication in that field. Research Interest Currently, Alharbi research is focused

Yahya Bokhari

Postdoctoral Research Fellow, Computer Science
Yahya Bokhari is a Postdoctoral Research Fellow at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST), working with Professor Wolfgang Heidrich on enhancing X-ray images under Smart Health Initiative. Education and Early Career Yahya Bokhari received his bachelor's degree in Medical Technology from King Abdulaziz University, KSA. He holds a Master's degree in Bioinformatics and a Ph.D. degree in Computer Science from Virginia Commonwealth University, USA. Research Interest Dr. Yahya Bokhari is mainly interested in Image Processing, Computer Vision

Xiang Li

Xiang Li is a Postdoc Researcher at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Mohamed Elhoseiny in the Vision-CAIR Group. Education and Work Experience Xiang Li joined KAUST as a Postdoc Researcher in Dec 2022. Before that, he was a Postdoc Researcher at the Multimedia and Visual Computing Lab (MMVC) at NYU Tandon and NYU Abu Dhabi from Oct 2019. He received a Bachelor's degree in Remote Sensing Science and Technology from Wuhan University in 2014 and a Ph.D. in Cartography and Geography Information System

Victor Escorcia

Research Scientist committed to innovating AI agents to empower creativity and increase productivity. Passionate about developing cutting-edge AI applications involving video understanding and creative storytelling. I have a wide range of research and engineering interests from on-device AI to General AI. Reach out!

Tarek H. Mahmoud

Areas of Expertise and Research Interests ​Computer Vision Machine Learning Robotics Education Profile ​MS in Electrical Engineering, King Abdullah University of Science and Technology (KAUST), Saudi Arabia (2017) ​​BS in Electrical Engineering, King Fahd University of Petroleum & Minerals (KFUPM), Saudi Arabia (2016)

Somayah Albaradei

Ph.D. Student, Computer Science
Somayah Albaradei is a Ph.D. student at Structural and Functional Bioinformatics Group (SFB) under the supervision of Professor Xin Gao at King Abdullah University of Science and Technology (KAUST). ​Somayah obtained her master's degree in computer science from the University of Manitoba, Canada in 2014. Professional Profile 2014: Lecturer at College of Computing and Information Technology-King Abdulaziz University - Jeddah - Saudi Arabia 2010- 2011: Teacher Assistant at College of Computing and Information Technology-King Abdulaziz University - Jeddah - Saudi Arabia 2009-2010: Collaborator

Silvio Giancola

Silvio Giancola is a Research Scientist at King Abdullah University of Science and Technology (KAUST), under the supervision of Prof. Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL), part of the Center of Excellence for Generative AI (GenAI).

Shuming Liu

Ph.D. Student, Computer Science
Shuming Liu is a Ph.D. student in the computer science program at the Image and Video Understanding Lab (IVUL), King Abdullah University of Science and Technology (KAUST), under the supervision of Professor Bernard Ghanem.

Shariq Farooq Bhat

M.S. Student, Computer Science
Shariq Farooq Bhat is an MS/PhD student under the supervision of Professor Peter Wonka at King Abdullah University of Science and Technology (KAUST). Education and Early Career Shariq Farooq Bhat obtained his bachelor of technology degree in Electronics & Communication Engineering from the National Institute of Technology Srinagar, India in 2018. During bachelor’s degree, he was an intern at Texas Instruments (TI) Center for Embedded Product Design at NSIT in New Delhi. Then, in 2016, he worked at the Indian Institute of Science (IISc) as a computer vision and deep learning research Intern and

Sara Rojas Martinez

Sara Rojas Martinez is a Ph.D. student in the KAUST Image and Video Understanding Lab (IVUL) under the supervision of Professor Bernard Ghanem. Before joining KAUST, Sara obtained a master’s degree in Biomedical Engineering from Universidad de Los Andes, Bogotá, Colombia. Research Interests Sara is interested in topics related to the investigation in Artificial Intelligence and Computer Vision. . Education Profile • M.S., Biomedical Engineering, University of Los Andes, Colombia, 2018 • B.E., Artificial Intelligence in Electronics Engineering, University of Los Andes, Colombia, 2017

Sara Shaheen

Sara Shaheen was a Ph.D. student in Computer Science under the supervision of Professor Bernard Ghanem at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). She is currently an Assistant Professor in Computer Science at Prince Sultan University (PSU) in Riyadh, Saudi Arabia. Education and Career Sara received her Bachelor degree in Computer Science from Prince Sultan University (PSU) in Riyadh in 2010. She joined the MS/PhD program in KAUST and earned her Master and Ph.D. in Computer Science in 2017. She was a part of Image and Video Understanding

Salman Alsubaihi

Salman Alsubaihi was an Electrical and Computer Engineering Master Student in the Image and Video Understanding Lab (IVUL) under the supervision of Professor Bernard Ghanem at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Salman Alsubaihi obtained his bachelor degree in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in Saudi Arabia in 2017. In 2019, he received his Master in Electrical Engineering from KAUST. Research Interests ​ Salman is focusing on understanding deep neural

Rui Li

Rui Li is an Electrical Engineering Ph.D. candidate in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at the Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Rui Li obtained bachelor of engineering degree in Telecommunication Engineering from Xidian University in China in 2013. After that in 2016, he received his master degree in Electrical Engineering from University of Science and Technology of China in 2016. Rui started his career life as a Research Assistant at State

Rameen Abdal

Ph.D. Student, Computer Science
Rameen Abdal is a Master student under the supervision of Professor Peter Wonka at King Abdullah University of Science and Technology (KAUST). He has graduated in 2023. Education and Early Career Rameen Abdal obtained his bachelor of technology degree in Electronics and Communications Engineering from the National Institute of Technology in Srinagar, India in 2018. After that, he joined KAUST for the MS/PhD program in computer science to continue his studies. Before joining KAUST, Rameen was an intern at Texas Instruments (TI) Center for Embedded Product Design at Netaji Subhas University of

Peter Wonka

Professor, Computer Science
Professor Peter Wonka is a computer scientist with a research focus in computer vision, computer graphics, remote sensing, and machine learning.

Qizhou Wang

Qizhou Wang is an M.S./Ph.D. candidate in the KAUST Primalight research group under the supervision of Professor Andrea Fratalocchi. Before joining KAUST, Qizhou obtained a bachelor's degree in communication engineering from the University of Electronic Science and Technology, China. Research Interests Qizhou's research interests include machine learning, optimization theories and computer vision.

Qian Wang

Ph.D. Student, Computer Science
Qian Wang is a MS/Ph.D. student at Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), studying under the supervision of Professor Peter Wonka in his research group. Education Qian Wang graduated with great distinction from Wuhan University with Bachelor's Degree. Research Interest Research interest of Qian Wang is Computer Vision.

Peihao Zhu

Ph.D. Student, Computer Science
Peihao Zhu is a Computer Science Ph.D. candidate at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Peter Wonka in his research group. He has completed his Ph.D and graduated in 2023. Education and Early Career Peihao Zhu obtained his bachelor of engineering in Automation from Northeastern University in China in 2016. After that, he continued his studies in Computer Science and received his master's degree from King Abdullah University of Science and Technology (KAUST) in Saudi Arabia in 2019. Research Interest

Peng Han

Ph.D. Student, Computer Science
Peng Han is a Ph.D. student in Computer Science program at Machine Intelligence and kNowledge Engineering (MINE) Laboratory under the supervision of Professor Xiangliang Zhang at King Abdullah University of Science and Technology (KAUST). Prior to that, he was a Research Associate in the School of Computer Science and Engineering, Nanyang Technological University (NTU) under the supervision of Prof. Aixin Sun, Singapore. He received his M.E. in Computer Science from Renmin University of China (RUC) at BDAI lab (leaded by Prof. Ji-rong Wen) in 2017. Research Interests ​Peng's research interests

Noor Bafageeh

Noor Bafageeh was a Master student in Computer Science Program under the supervision of Professor Bernard Ghanem at Visual Computing Center (VCC) at King Abdullah university of Science and Technology (KAUST). Education and Career Noor earned her bachelor degree in Computer Science from Effat University in Jeddah in 2016. She joined KAUST and received her master degree in Computer Science in 2018. Research Interest She is interested in computer vision, machine learning, Generative Adversarial Networks (GAN) and deep learning. Education Profile M.S., Computer Science, King Abdullah University of

Neil Smith

Research Scientist, Computer Science
Neil Smith is a Research Scientist in the Computational Imaging Group (VCCIMAGING) working with Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Neil joined University of California in San Diego (UCSD) at the start his academic journey. He obtained his bachelor degree in Anthropology with Concentration in Archaeology in 2001. After that in 2003, he received his master degree in Anthropology. He has a doctoral in Anthropology since 2009. Dr. Smith started his career life as a Geographic Information Systems (GIS) Specialist at

Motasem Alfarra

Motasem Alfarra is an Electrical and Computer Engineering Ph.D. student in Image and Video Understanding Lab (IVUL) Group in Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem.

Mojtaba Alshams

KAUST-CEMSE-CS-Vision-CAIR-Mohamed-Elhoseiny

Mohamed Elhoseiny

Associate Professor, Computer Science
Professor Elhoseiny’s research focuses on developing affective artificial intelligence that understands and generates novel visual content. He has contributed to and led numerous seminal works of affective AI art creation.

Modar Alfadly

Ph.D. Student, Computer Science
Modar Alfadly is a Ph. D. candidate in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at KAUST. Education and Early Career Alfadly received his bachelor’s degree in Software Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in 2016. A year later, he obtained his master’s degree in Computer Science and successfully defended his thesis, titled “Analytic Treatment of Deep Neural Networks under Additive Gaussian Noise”. Research Interest Modar Alfadly is focusing on understanding deep neural networks to build more intelligent

Merey Ramazanova

Ph.D. Student, Computer Science

Mengmeng Xu (Frost)

Mengmeng Xu (Frost) was an Electrical and Computer Engineering PhD Student in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. He is currently continuing his Ph.D. Education and Early Career Mengmeng obtained his bachelor's degree in Optics and Optical Sciences from Zhejiang University in China in 2017 and his Master's Degree from KAUST under the supervision of Professor Bernard Ghanem. Research Interests He is mainly focusing on problems that arise in computer vision, including

Matthias Mueller

Matthias Mueller was an Electrical and Computer Engineering Ph.D. candidate in Image and Video Understanding Lab (IVUL) Group at Visual Computing Center (VCC) under the supervision of Prof. Bernard Ghanem at King Abdullah University of Science and Technology (KAUST). Education and Early Career Matthias graduated with a B.Sc. in Electrical Engineering and Math Minor from Texas A&M University in 2011. After graduation, he joined P+Z Engineering in Munich, Germany as an Electrical Engineer and worked for 3 years on the development of mild-hybrid electric machines at BMW. In 2014, he started his M

Matheus Vinícius Medeiros de Souza

Ph.D. Student, Computer Science
Matheus Vinícius Medeiros de Souza is an MS/Ph.D. candidate in the KAUST Computational Imaging Group under the supervision of Professor Wolfgang Heidrich. Before joining KAUST, Matheus obtained a bachelor's degree in electrical engineering from the Federal University of Rio Grande do Norte, Brazil. Research Interests Matheus's research interests include Computer Vision and Machine learning.

Masheal Alghamdi

Masheal Alghamdi is a Ph. D. candidate in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Masheal obtained her bachelor degree in Computer Science from King Abdul-Aziz University (KAU) in Jeddah, Saudi Arabia in 2009. After that she joined KAUST to receive her master degree in Computer Science in 2014. Masheal is a researcher in the National Center for Computation Technology and Applied Math (CTAM) at King Abdul-Aziz City for Science and Technology (KACST)

Lama Alssum

Ph.D. Student, Computer Science
Lama Alssum is a Ph.D. student in Computer Science under the supervision of Professor Bernard Ghanem in Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Early Career Lama studied Information technology at King Saud University (KSU) in Riyadh and graduated with a Bachelor degree in 2011. After her bachelor degree, she joined KSU as a Teaching Assistant. Later on, she continued her studies and earned her Master degree in Computer Science from the School of Computing Science at the University of Glasgow, United Kingdom. Lama first joined

Kumail Alhamoud

M.S. Student, Computer Science
Kumail Alhamoud is a Computer Science M.S Student at KAUST working under the supervision of Professor Bernard Ghanem at the Image and Video Understanding Lab (IVUL). Before joining KAUST, Kumail obtained his B.S in Electrical and Computer Engineering at Cornell University in 2021. His current research interests include continual learning, learning from limited data under distribution shifts, and AI for Science and Biomedicine. Publications

Kilichbek Haydarov

Ph.D. Student, Computer Science
Kilichbek Haydarov is a M.S./Ph.D. candidate at the KAUST Computer Vision, Content AI research group under the supervision of Professor Mohamed Elhoseiny. Before joining KAUST, Kilichbek obtained a bachelor's degree in computer science and engineering from Sejong University, South Korea. Education and early career Kilichbek Haydarov obtained his bachelor’s degree from Sejong University in 2020 February (Seoul, South Korea). His major was Computer Science and Engineering. During his undergraduate years, he was working in Intelligent Media Lab and focusing on anomaly detection and action

Khaled Abu-Jbara

Khaled Abu-Jbara was a Ph. D. student in the Computational Imaging Group (VCCIMAGING) under the supervision of Professor Wolfgang Heidrich at King Abdullah University of Science and Technology (KAUST). Education and Early Career Khaled Abu Jbara received his bachelor degree in Electrical Engineering, with Distinction, First Class Honors, from Kuwait University (KUNIV), Kuwait in August 2011. He worked as an Administrative Engineer and Teacher Assistant at Kuwait University, Electrical Engineering Department. After that, he joined King Abdullah University of Science and Technology (KAUST) as a

Kai Yi

Ph.D. candidate working on machine learning optimization, LLMs and federated learning.

Juan C. Pérez

Juan C. Pérez was a Ph.D. Candidate in the computer science program under Professor Bernard Ghanem's supervision at the Image and Video Understanding Lab at King Abdullah University of Science and Technology (KAUST). Before joining KAUST, Juan obtained a master's degree and a bachelor's degree ( cum laude) in biomedical engineering from Universidad de Los Andes, Colombia.

Juan Pablo Peña (Student)

Juan Pablo Peña is part of the Visiting Students Research Program at King Abdullah University of Science and Technology (KAUST). During his Internship, he is conducting his research at the Sensors Lab, in the Electrical Engineering Department, CEMSE, KAUST. Education and Early Career Juan Pablo Peña graduated from Mecatronichs Engineering B.S. at the National Autonomous University of Mexico, Mexico City on May 2019. Additionally, on 2019 summer he worked on an augmented reality simulation for visual impairments created during his research internship at Ryerson University, Canada. Similarly, on

Jia-Hong Huang

Jia-Hong Huang was a Master's student in the Electrical and Computer Engineering Program under the supervision of Professor Bernard Ghanem at Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). Education and Career Jia-Hong earned a double major bachelor's degree in Statistics and Mathematical Science from National Chengchi University in Taiwan in 2014. He received his master's degree in Mechanical Engineering from National Taiwan University in 2016. After that, he joined KAUST and received his second master's degree in Electrical Engineering in 2018

Jean Lahoud

Jean Lahoud was a Ph. D. student in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at KAUST. Education and Early Career Jean Lahoud received his Bachelor of Engineering in Mechanical Engineering from Notre Dame University in Lebanon in 2012. In 2014, he obtained his Master of Engineering degree in the same field from American University of Beirut in Lebanon. Before joining KAUST, Jean was a product manager at Murex systems in Lebanon. Research Interest Jean Lahoud is interested in 3​D scene understanding using RGB-D sensors. Honors and Awards In

Jesus Zarzar

Jesus Zarzar was an Electrical and Computer Engineering PhD student in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. Education and Early Career Jesus obtained his bachelor degree in Electrical and Computer Engineering from UT Austin, United States in 2017 before obtaining his Master's Degree from KAUST under the supervision of Professor Bernard Ghanem. Publications Education Profile ​B.S., Electrical and Computer Engineering, UT Austin, Austin, United States, 2017

Ivan Skorokhodov

Ph.D. Student, Computer Science
Ivan Skorokhodov is a Ph.D. candidate in the Computer Science Program under the supervision of Professor Peter Wonka at Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST). His research interests include such areas of deep learning as generative models, hypernetworks and neural rendering. Ivan Skorokhodov has obtained his Ph.D degree and graduated in March 2023. Education and Early Career Ivan obtained his bachelor's degree in Management from the Moscow Engineering Physics Institute in 2014. He continued his studies there and received his master's degree

Humam Alwassel

Ph.D. Student, Computer Science
Humam Alwassel is a Computer Science Ph.D. candidate in Image and Video Understanding Lab (IVUL) Group under the supervision of Professor Bernard Ghanem at King Abdullah University of Science and Technology (KAUST). Education and Early Career Humam obtained his bachelor degree with double major in Computer Science and Mathematics from Cornell University in New York, USA in 2016. After that, he joined KAUST for the MS/PhD program and received his master degree in Computer Science in 2018. Research Interest He’s currently focused on the development of novel computer vision techniques for video

Hasan Abed Al Kader Hammoud

Hasan is an Electrical and Computer Engineering MS/Ph.D. student in Image and Video Understanding Lab (IVUL) Group in Visual Computing Center (VCC) at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. Education and Early Career Hasan obtained his bachelor's degree in Electrical and Computer Engineering from American University of Beirut in 2020. He joined KAUST in 2020 to pursue his MS and PhD degrees. Research Interest Deep Learning Machine Learning Computer Vision Publications Rapid Adaptation in Online Continual Learning: Are We

Hajer Abbas

Visiting Student (former), Electrical and Computer Engineering
Visiting Student in the Electrical Engineering Department, CEMSE, King Abdullah University of Science and Technology (KAUST).

Habib Slim

Ph.D. Student, Computer Science
Habib Slim is a Computer Science Ph.D. candidate at the Visual Computing Center (VCC)/Vison-CAIR at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Mohamed Elhoseiny Education: M.Sc Data Science, Grenoble Institute of Technology, France, 2021 M.Eng Applied Mathematics and Computer Science, Grenoble Institute of Technology, France, 2021

Gordon Guocheng Qian

Guocheng Qian is currently working towards an MS/Ph.D. degree in the Department of Computer Science at King Abdullah University of Science and Technology (KAUST). He is part of the Image and Video Understanding Lab (IVUL), supervised by Prof. Bernard Ghanem. During his Ph.D. studies, he interned at several leading institutions including Snap Research, Meta Reality Lab, and MEGVII research. His primary research interest lies in 3D vision. Education and Early Career Guocheng obtained his bachelor's degree in Engineering with first-class honors from Xi’an Jiaotong University (XJTU) in China in

Guohao Li

Ph.D. Student, Computer Science
Guohao Li is a Ph. D. candidate in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at KAUST. Education and Early Career Guohao Li obtained a Bachelor’s Degree in Communication Engineering from Harbin Institute of Technology in China in 2015. In 2018, he received his Master Degree in Communication and Information System from Chinese Academy of Science in China. Research Interest His primary research interest is in Computer Vision and Deep Learning. Publications Education Profile M.Sc. in Communication and Information System, Chinese Academy of

Ganesh Sundaramoorthi

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

Frankly Toro

Frankly Toro is a Ms/Ph.D. student under the supervision of Prof. Bernard Ghanem at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career He is a graduate of National University of Colombia where he received a B.S. degree in Mechatronics. Education Profile B.S., Mechatronics , National University of Colombia, 2020

Fabian Heilbron

Fabian Caba Heilbron was a Ph.D. student in Image and Video Understanding Lab (IVUL) Group under the supervision of Prof. Bernard Ghanem at King Abdullah University of Science and Technology (KAUST). He is currently a Research Scientist at Adobe Research in San Jose, California. Education and Early Career Fabian has a Bachelor’s Degree in Electronics Engineering from Universidad del Norte in Barranquilla, Colombia, 2011. In 2013, he received his Master Degree in Electronics Engineering from Universidad del Norte in Barranquilla, Colombia. He joined KAUST as a Ph.D. candidate and received his

Chen Zhao

Chen Zhao is a Research Scientist at KAUST, and Lead of the Video Understanding Theme in the Image and Video Understanding Lab. She received her Ph.D. degree from Peking University, China in 2016. She studied in University of Washington, US from 2012 to 2013, and at the National Institute of Informatics, Japan in 2016. She has published 40+ papers on representative journals and conferences such as TPAMI, CVPR, ICCV, ECCV, and has received over 3000 citations according to Google Scholar.

Cheng Zheng

Cheng Zheng is a Software Engineer Consultant working with Professor Bernard Ghanem in the Image and Video Understanding Lab (IVUL) in the Visual Computing Center at King Abdullah University of Science and Technology (KAUST). Education and Early Career Cheng Zheng received his Bachelor's degree in Computer Science from Beijing University of Posts and Telecommunications (BUPT), China, in 2009. He received his Master's degree from the University of Chinese Academy of Sciences (UCAS), China, In 2012. Before joining KAUST, in 2012, he worked as a software engineer at NetEase Games in China. In

Caigui Jiang

Research Scientist, Computer Science
Caigui Jiang is a Research Scientist at the Visual Computing Center (VCC) working with Professor Helmut Pottmann at King Abdullah University of Science and Technology (KAUST). Education and Early Career Dr. Jiang obtained a bachelor degree in Electronic Engineering and his masters in Pattern Recognition and Intelligent Systems from Xi'an Jiaotong University (XJTU) in China. After that, he joined KAUST to receive his Ph.D. in Computer Science in 2016. Caigui has a diverse experience in the academic and research field. In 2016, he joined Max Planck Institute for Informatics as a Postdoctoral

Carlos Hinojosa Montero

Postdoctoral Research Fellow, Image and Video Understanding Lab
Education and Early Career o Bachelor of System Engineering and Informatics, University: Universidad Industrial de Santander, 2011-2015. o Master of Science in Computer and System Engineering, University: Universidad Industrial de Santander, 2016-2018. o PhD in Computer Science, University: Universidad Industrial de Santander, 2017-2022.

Boris Radovic

Boris Radovic is a Ph.D. candidate in the computer science program, under the supervision of Professors Marco Canini and Veljko Pejović, and is a member of the Software-defined Advanced Networked and Distributed Systems (SANDS) Lab. He holds a Bachelor of Science (B.Sc.) in Computer Science and a Master of Science (M.Sc.) in Data Science, both obtained from the Faculty of Computer and Information Science at the University of Ljubljana, Slovenia. During his academic journey, Boris gained experience across diverse computer science domains through his long-term collaboration with the Laboratory

Ali Thabet

Ali Thabet is a Research Scientist at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST), working with Professor Bernard Ghanem in the Image and Video Understanding Laboratory (IVUL). Education and Early Career Ali obtained a bachelor of engineering degree in Electrical Engineering, from the American University of Beirut in Beirut, Lebanon in 2006. He holds a ​Ph.D. in Computer Science from the University of Dundee in Dundee, UK. He joined KAUST as a Postdoctoral Fellow in the Visual Computing Center (VCC) from 2012 to 2014. After that, he worked as

Alejandro Pardo

Alejandro Pardo is a Ph.D. candidate in the Electrical and Computer Engineering (ECE) program under the supervision of Professor Bernard Ghanem at King Abdullah University of Science and Technology (KAUST) in Saudi Arabia.

Ahmed S. Abdelreheem

Ahmed Abdelreheem is a Computer Science MS. student at the Visual Computing Center (VCC) in King Abdullah University of Science and Technology (KAUST). Education and Early Career Ahmed Abdelreheem is a graduate of Cairo University, where he received a B.S. degree in Computer Engineering in 2019. Research Interest Ahmed focuses on Computer Vision and Machine Learning. Education Profile BSc., Computer Engineering, Cairo University, Egypt, 2019

Abdurauf Abdurakhmanov

Adel Bibi

Adel Bibi is a postdoctoral research assistant in computer vision and machine learning at the Torr Vision Group working with Professor Philip Torr at the University of Oxford. Prior to that, he received his MSc and PhD degrees from King Abdullah University of Science & Technology (KAUST) where he was part of the Image and Video Understanding Lab (IVUL) advised by Professor Bernard Ghanem. Education and Early Career Adel Bibi has a Bachelor’s Degree in Electrical Engineering from Kuwait University in 2014. He received his Master Degree in Electrical Engineering from King Abdullah University of

Abdullah Hamdi

Abdullah Hamdi is a Ph.D. candidate in Image and Video Understanding Lab (IVUL) Group at King Abdullah University of Science and Technology (KAUST) under the supervision of Professor Bernard Ghanem. Education and Early Career In 2016, Abdullah Hamdi obtained his bachelor degree in Electrical Engineering from King Fahd University of Petroleum and Minerals (KFUPM) in Dhahran, Saudi Arabia. After that, he joined KAUST to proceed in the same field of study and received his master degree in 2017 in Computer Vision track. Research Interest Machine Learning Robustness of Deep Learning Computer Vision