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    Mohamed Souiai

    Principle Computer Vision Engineer at Magic Leap

    Dr. Mohamed Souiai is a highly accomplished individual with a Ph.D. in Computer Vision from the Technical University of Munich. Throughout his academic journey, he has published more than 15 papers in the fields of computer vision and medical imaging, showcasing his expertise in various areas of research and application.

    During his time at the Computer Vision Lab under the guidance of Prof. Daniel Cremers, Dr. Souiai honed his skills across a wide spectrum of computer vision topics, including discrete and convex optimization, semantic multi-label image segmentation algorithms, GPU parallel programming using CUDA, 3D motion estimation and segmentation, image processing techniques like de-noising and super-resolution, and MRI reconstruction using variational methods.

    Dr. Souiai also has experience in developing highly efficient algorithms for multi-labeling problems, real-time 3D scene flow, and 3D motion estimation. His expertise extends to areas such as large-scale depth algorithms on GPUs, improving multi-view 3D/4D reconstruction utilizing Shannon's entropy, and a fundamental understanding of deep learning principles.

    With a Master's degree in Computer Science from The University of Bonn, Dr. Souiai has a strong educational background that complements his hands-on experience in the industry. He has held pivotal roles at Magic Leap, including Principal Computer Vision Engineer, Lead Computer Vision Engineer, and Senior Computer Vision Engineer.

    His previous engagements as a Ph.D. Student at TU München and Research Intern at both the University of Bonn and Fraunhofer Institute for Systems and Innovation Research ISI have equipped him with a diverse skill set and a deep understanding of the intricacies of computer vision and related fields.

    Mohamed Souiai
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    Location

    Switzerland