Omar Tahri

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About

Omar Tahri is a researcher working at the intersection of computer vision, robotics, and medical imaging, with contributions spanning intelligent sensing, 3D reconstruction, and autonomous navigation systems. His work bridges multiple domains, demonstrating a versatile research profile with both applied and theoretical dimensions. Among his most recognized contributions is his 2021 work on visual-tactile fusion for 3D object reconstruction, which addresses a fundamental limitation in robotic perception — the inability to capture occluded surface information from visual sensing alone. By combining depth imaging with gripper touch data, Tahri's approach enhances robotic manipulation and grasping planning, earning 10 citations and positioning him as a contributor to multimodal sensing in robotics. More recently, his 2024 research on self-supervised monocular pose and depth estimation for wireless capsule endoscopy leverages transformer-based architectures to advance diagnostic capabilities within the gastrointestinal tract — a medically critical and technically challenging domain. This work reflects his growing interest in applying cutting-edge deep learning methods to healthcare robotics. Though early in citation accumulation, Tahri's research demonstrates a thoughtful integration of robotics, sensing technologies, and medical applications, making him a researcher worth following as these fields continue to converge.