Call me Os
Switzerland 🇨🇭
Reality Labs
Mohamed Abdelfattah
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OSMO introduces egocentric self-emotion tracking with a large-scale dataset, a multi-task benchmark, and OSIRIS, a multimodal model for coherent emotion timelines.
Mohamed Abdelfattah*
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OSKAR is a self-supervised multimodal foundation model that learns in the latent space by predicting masked multimodal features.
Mohamed Abdelfattah
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MaskCLR improves the robustness of transformer-based action recognition methods against noisy and incomplete skeletons.
Mohamed Abdelfattah
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S-JEPA is an instantiation of JEPA for self-supervised skeletal action recognition.
We take a step towards computer-aided waste detection and present the first in-the-wild industrial-grade waste detection and segmentation dataset, ZeroWaste.
This paper introduces ArtELingo, a new benchmark and dataset, designed to encourage work on diversity across languages and cultures.
Mohamed Abdelfattah
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A computer-vision pipeline using conventional 2D sleep-lab cameras to automatically detect iRBD from REM movement dynamics with up to 91.9% accuracy.
A machine-learning human thermo-physiology model (ML-HTPM) developed to predict thermal response.
In this study, we applied multi-modal non-intrusive computer vision algorithms to extract personal features defining human thermal comfort.
A curated collection of milestones and recognitions.
Awarded the AUC PA Cup for the class of 2022 for top academic and extracurricular achievements.
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High Academic Achievement (Top 10% of Graduating Class) in SSE Honours Assembly.
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Undergraduate Research Award, 4,000 USD.
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Ranked among the top 10 ROV teams in the Middle East.
MATE ROV Regional Competition
Ranked 1st in the CSCE programming contest.
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Named Highest Achiever and Reader of the Year.
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Instructional roles showcased by course focus, not timeline order.
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EPFL
I am always happy to discuss research collaborations, internships, and full-time opportunities in computer vision and multimodal learning. If you are hiring, collaborating, or want to chat about ideas, feel free to reach out.