PhD Researcher in Artificial Intelligence & Big Data | Quantum Neural Network | Robotics & STEM Coach

I am a PhD researcher specializing in Artificial Intelligence and Big Data, with a particular focus on Quantum Machine Learning and Quantum Neural Networks. My academic research centers on hybrid quantum-classical models for nonlinear function approximation, leveraging Python-based frameworks such as Qiskit and PennyLane. I have a strong foundation in machine learning, deep learning, data science, and computer vision, complemented by hands-on experience in robotics education and STEM coaching.

Throughout my academic journey, I have developed and implemented quantum neural network models, comparing classical multilayer perceptrons with quantum-inspired approaches. My master’s thesis involved creating a deep learning-based image segmentation system for underwater waste detection, applying computer vision techniques to environmental monitoring. I am proficient in Python, TensorFlow, PyTorch, OpenCV, and other relevant tools.

I am passionate about advancing research in AI and quantum computing and am actively seeking international research collaborations, funded PhD opportunities, and remote roles in AI/ML research. Additionally, I am committed to STEM education, teaching robotics and programming concepts to students aged 17 to 22, and mentoring teams in national and international robotics competitions.

My technical skills include Python, SQL, Git, Linux, machine learning frameworks, quantum machine learning libraries, and robotics platforms. I am fluent in Arabic and French, with advanced English proficiency, particularly in research and technical communication.

I bring strong problem-solving abilities, critical thinking, and effective communication skills to my work, along with a collaborative mindset and adaptability. I am eager to contribute to cutting-edge AI research and foster the next generation of STEM talent through education and mentorship.