Profiles

Professor Bernard Ghanem is the Chair of the KAUST Center of Excellence for Generative AI (GenAI) and a leading expert in computer vision and machine learning. He is a professor of Electrical and Computer Engineering (ECE) and the principal investigator of the Image and Video Understanding Lab (IVUL).

Ghanem's research focuses on computer vision and machine learning, particularly on large-scale video understanding, 3D scene comprehension and the foundation of machine learning.

At KAUST, Professor Ghanem's work bridges academic innovation and industry needs, advancing AI technologies through interdisciplinary collaborations. As Chair of the KAUST Center of Excellence for Generative AI, he leads efforts to establish world-leading excellence in GenAI research by developing the next generation of models that are efficient, trustworthy and tailored for widespread deployment.

His work supports solutions for the Kingdom's national Research, Development, and Innovation (RDI) priorities—Health and Wellness, Sustainability and Essential Needs, Energy and Industrial Leadership, and Economies of the Future—while accelerating the adoption of GenAI through translational research and talent development in collaboration with industry partners.

Professor Ghanem earned his Ph.D. in Electrical and Computer Engineering in 2010 and his M.Sc. in 2008, both from the University of Illinois at Urbana-Champaign (UIUC), U.S. He served as a graduate research assistant at the Computer Vision and Robotics Lab (CVRL) at the Beckman Institute for Advanced Science and Technology at UIUC.

Professor Ghanem’s research interests and expertise lie in:

1. Robust, large-scale video understanding, including object tracking, activity recognition/detection, and retrieval.
2. Visual computing for automation, including 3D object detection, 3D tracking, 3D indoor and outdoor navigation, and Sim2Real transfer learning.
3. Development and analysis of foundational tools in computer vision and machine learning, including deep graph neural networks, neural network robustness and certification (Trustworthy AI), continual learning, and foundational models in vision and language.

Her research interests include computer vision and deep learning, with a focus on video understanding and efficient models.

Silvio Giancola received his Master Degree in Mechatronics Engineering Institut National des Sciences Appliquées (INSA), Strasbourg in France in 2012. He has a Ph.D. in Mechanical Engineering from Politecnico di Milano, Milano, Italy.

Before joining KAUST, Silvio had academic experience in Politecnico di Milano in Italy. He was a teaching assistant for undergraduate and graduate students in Industrial and Information Engineering School, Politecnico di Milano in Italy from 2014 until 2017. In addition to teaching, he was a Research Fellow who later on became a Postdoctoral Fellow.

At KAUST, Silvio was a Postdoctoral Fellow from 2017 to 2020, then became a Research Scientist since 2020. In 2022, Silvio co-founded the start-up Thya Technology, with which he won the TAQADAM accelerator program.

Silvio Giancola is mainly interested in Computer Vision, Deep learning, Sports, and Robotics.

PhD from Peking University in 2021; Research Scientist in JD Explore Academy from 2021 to 2023.

machine learning, large language/vision models, trustworthiness

Andres Villa received a bachelor's in Electronic Engineering at Universidad del Norte in Barranquilla, Colombia, in 2017. Moreover, he received his PhD in Computer Science at Pontifical Catholic University in 2023 in Santiago, Chile. Before joining KAUST, Andres was a teaching assistant for undergraduate and graduate students in the Engineering department at Pontifical Catholic University in Chile from 2019 until 2024. He was teaching subjects such as Deep Learning and AI Applications (VQA, Image Captioning, and Video Understanding). Andres was a Research Intern at IVUL from June 2021 to June 2022.

Andres focuses on Computer Vision, Continual Learning, Video Understanding, and Visual Language Models.

Bing Li received her bachelor’s degree in Computer Science from Jinan University, Guangzhou, China, in 2009. She holds a Ph.D. degree from the Institute of Computing Technology, Chinese Academy of Sciences, Beijing, China in 2016.

In 2016, Bing Li worked as a Postdoc Fellow at the University of Southern California, USA, before joining KAUST.

She is mainly interested in Visual Content Analysis and Processing, Computer Vision and Machine Learning.

Computer Vision, Machine Learning, Computational Imaging, Multidimensional Signal Processing, and Image/Video Understanding.

I completed my Ph.D. at the University of Amsterdam, advised by Prof. Cees Snoek. My area of interest is Video Understanding, with my PhD thesis focusing on Video-Efficient Foundation Models. I am particularly interested in training foundation models via self-supervised learning from multiple modalities of the video data.

Computer Vision, Video Understanding, Self-supervised Learning, Video Foundation Models.

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. She earned her PhD in Engineering, MSc in Electronic Engineering, and a Bachelor’s degree in Energy Engineering in Colombia.

Her research interests include video understanding, domain adaptation, generative AI, and preserving patient privacy, with a focus on deep learning, machine learning, and artificial intelligence for healthcare applications.

Computer Vision, Edge Machine Learning, Generative Modeling.

Aznaur obtained his bachelor's degree in Applied Mathematics and Physics from Moscow Institute of Physics and Technology in 2023. He joined KAUST in 2024 to pursue his MS and PhD degrees.

Deep Learning, Computer Vision, Reinforcement Learning.

Hani Al Majed has a Bachelor's degree in Electrical Engineering from the University of Illinois at Urbana-Champaign (2019–2023) and is currently pursuing a Master's in Electrical and Computer Engineering at KAUST (2023–2025) under the supervision of Professor Bernard Ghanem. His career includes internships at IBM, the National Center for Supercomputing Applications (NCSA), Discovery Partners Institute, and KAUST, where he worked on projects related to variational quantum models, 3D body reconstruction, sequence learning for epidemiological forecasting, and applications of physics-informed neural operators.

Hani's current research interests encompass machine learning workflow automation, physics-informed neural operators, AI for Science and chemistry.

Research Interests

Motasem is interested in computer vision, machine learning, and continual learning.

• Long-Form Video Understanding.
• Temporal Action Detection, Action Recognition.
• Video-Language Grounding.

I am currently pursuing a Ph.D. in Computer Science at King Abdullah University for Science and Technology (KAUST), under the supervision of Prof. Bernard Ghanem. My research focuses on applying machine learning to solve real-world challenges, with an emphasis on efficient training and inference of models. This includes improving data, training, and model efficiency to create more scalable and effective solutions. I hold an M.S. in Computer Science from KAUST and a B.S. in Electrical and Computer Engineering from Virginia Tech. I have over 7 years of experience in automation systems prior to starting my M.S. degree.

I am interested in exploring techniques for efficient training and inference of machine learning models, with a focus on improving data efficiency, training efficiency, and model efficiency.

She holds a Master’s Degree in Data Science from the University of Jeddah and a Bachelor's Degree in Computer Science with a specialization in Software Engineering from King Abdulaziz University. She began her career as a Digital Repository Coordinator at King Abdullah University for Science and Technology (KAUST), where she was responsible for developing data analysis algorithms and building data models. Later, she transitioned to the role of Data Science Coordinator and Teaching Assistant at the SDAIA-KAUST Center of Data Science & AI, where she focused on AI content development, automation, and machine learning training initiatives.

Her research interests focus on generative AI, vision/text multimodality, and deep learning

Research Scientist based in Cambridge (UK). Victor works at the Samsung AI Center, focusing on enhancing AI applications in creative and productivity domains. I earned my BSc and MSc in Electrical Engineering from Universidad del Norte, studying under the supervision of Ph.D Juan Carlos Niebles. Victor completed his PhD at KAUST under the mentorship of Prof. Bernard Ghanem, with a research focus on computer vision. My early career was marked by pioneering developments in efficient video and action understanding models. Once I joined industry, I am committed to developing advanced AI applications that empower human creativity and scale General AI, particularly in edge computing environments.

My research spans a wide array of AI disciplines, with a special focus on computer vision, efficient video understanding, and the development of AI agents with a strong interest for edge deployment. I am particularly passionate about build AI Agents to enhance human creativity and productivity. My ongoing projects aim to seamlessly integrate AI capabilities into user-centric applications, pushing the boundaries of what AI can achieve in real-world scenarios.