I am a Computer Science and Engineering undergraduate at the Egypt-Japan University of Science and Technology (E-JUST), specializing in computer vision, deep learning, and pattern recognition. I published my first research paper in IEEE Xplore, DeepCat: A Deep Learning Approach to Understand Your Cat’s Body Language, where I designed architectures for analyzing feline emotions using YOLOv8, Python, and classification techniques. Currently, I am a Graduation Project Mentee at Microsoft Egypt Development Center, working with senior applied scientists to improve cultural awareness in Vision-Language Models (VLMs). My work involves benchmarking multiple VLMs on culture-specific datasets and evaluating their semantic performance using advanced NLP metrics. I have also developed several AI-driven projects, including a workout form assessment system using GRU models and real-time pose estimation, a lip-reading model powered by LSTMs and deep learning techniques, and StyleSync, a GAN-based style transfer platform enhanced with Siamese networks. My technical expertise includes Python, C/C++, PyTorch, TensorFlow, and OpenCV, alongside strong foundations in data processing and model-based design. I have achieved recognition in international competitions, ranking among the Top 9 teams in the MathWorks MiniDrone Competition (EMEA) and securing 3rd prize in the OpenCV Competition. I am passionate about bridging advanced AI research with real-world applications, with a strong interest in computer vision, multimodal AI, and culturally adaptive machine learning systems.…I am a Computer Science and Engineering undergraduate at the Egypt-Japan University of Science and Technology (E-JUST), specializing in computer vision, deep learning, and pattern recognition. I published my first research paper in IEEE Xplore, DeepCat: A Deep Learning Approach to Understand Your Cat’s Body Language, where I designed architectures for analyzing feline emotions using YOLOv8, Python, and classification techniques. Currently, I am a Graduation Project Mentee at Microsoft Egypt Development Center, working with senior applied scientists to improve cultural awareness in Vision-Language Models (VLMs). My work involves benchmarking multiple VLMs on culture-specific datasets and evaluating their semantic performance using advanced NLP metrics. I have also developed several AI-driven projects, including a workout form assessment system using GRU models and real-time pose estimation, a lip-reading model powered by LSTMs and deep learning techniques, and StyleSync, a GAN-based style transfer platform enhanced with Siamese networks. My technical expertise includes Python, C/C++, PyTorch, TensorFlow, and OpenCV, alongside strong foundations in data processing and model-based design. I have achieved recognition in international competitions, ranking among the Top 9 teams in the MathWorks MiniDrone Competition (EMEA) and securing 3rd prize in the OpenCV Competition. I am passionate about bridging advanced AI research with real-world applications, with a strong interest in computer vision, multimodal AI, and culturally adaptive machine learning systems.WWWW…