multimodal AI

Osama N. Hassan

Postdoctoral Research Fellow

Computer Vision multimodal AI Vision-Language Models agentic AI systems AI Safety and Reliability computational imaging

Postdoctoral Fellow in the Image and Video Understanding Lab (IVUL) at KAUST, working with Prof. Bernard Ghanem. His research spans computer vision, vision-language and multimodal models, and agentic AI systems, informed by a background ranging from optical sensing and computational imaging to machine learning for perception and AI systems that reason and act.

Mumtozbek Akhmadjonov

Ph.D. Student, Computer Science

Physical AI Embodied AI Generative AI and LLMs VLA multimodal AI

Currently researching robotic manipulation using planning with world models.

Yuqian Fu

Postdoctoral Research Fellow, Computer Science

egocentric video Video Understanding Long-Form Video Understanding multimodal AI few-shot learning

Yuqian Fu's research topics are computer vision and deep learning. She mainly aims to build more generalizable vision models by addressing challenges that arise when applying them to downstream tasks,

Adonai Vera

Intern, Image and Video Understanding Lab

Computer Vision Advanced Perception multimodal AI deep learning

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.