Hassan Chreif

As part of the Cedric Laboratory at Le Cnam, I am contributing to research and development in the field of 5G and New Radio (NR) systems. My work focuses on implementing high-performance networking functions on FPGAs to enhance real-time data processing and system responsiveness. I am also exploring task scheduling strategies and computation offloading mechanisms from general-purpose local processing units (CPUs) to reconfigurable hardware accelerators (FPGAs), aiming to optimize system efficiency, latency, and energy consumption. Key responsibilities: Design and hardware implementation of 5G/NR-related networking functions on FPGA platforms. Development of task offloading frameworks between CPU and FPGA. Analysis and optimization of processing pipelines for real-time communication systems. Collaboration with research teams on FPGA-based acceleration for wireless communication protocols.

Leading the development of an AI-powered product designed to automate refereeing in tennis using advanced computer vision techniques for ball and player detection, tracking, and triangulation. Implementing robust data pipelines in Azure and AWS to process and analyze real-time video data streams. Collaborating with cross-functional teams to integrate machine learning models into production systems. Optimizing data storage and retrieval processes to ensure high availability and low latency for real-time decision- making applications.

Designed and implemented a generative AI algorithm specifically for the creation of 3D Minecraft structures. Worked collaboratively with the development team to seamlessly integrate AI features into the game's existing systems, ensuring a cohesive user experience. Led rigorous testing and debugging processes to ascertain the reliability and efficiency of AI models, significantly improving project quality

I played a pivotal role in leveraging data to inform strategic decisions. Employing advanced analytical tools and techniques, I contributed to the extraction, cleaning, and interpretation of complex datasets. My responsibilities included creating insightful visualizations and comprehensive reports, aiding in effective decision-making processes. Collaborating closely with cross-functional teams, I applied statistical methods to derive actionable insights and presented findings to key stakeholders. This experience not only honed my technical skills in data analysis but also enhanced my ability to thrive in a collaborative, fast-paced professional environment.