About Me

Jimmy's journey into the world of Machine Learning and Scalable Systems is a testament to his passion and expertise in the field. Holding a Master’s degree in Cloud Computing and Large-Scale Systems from Université de Rennes, with a minor in Innovation and Entrepreneurship, he has developed a strong foundation in distributed computing and deep learning. His dedication to pushing the boundaries of scalable systems is evident in his contributions to energy-efficient machine learning models and cutting-edge reverse engineering techniques.

During the IMT Atlantique Rennes internship in the summer of 2023, Jimmy played a pivotal role in a research project aimed at reducing the energy consumption of 4G and 5G base stations in France using machine learning techniques. His involvement included redesigning the EARTH model, which enabled more accurate predictions of power consumption and the identification of key influencing factors. His innovative approach led to a remarkable 20% reduction in energy consumption at a base station in Rennes. This work reflects not only his technical prowess but also his commitment to sustainable, impactful solutions for real-world problems. You can explore the project here, supervised by Pr. Loutfi NYAUMI and Christopher Merlhe.

In 2024, Jimmy completed a six-month internship at Serma Safety and Security, where he focused on developing a Computer Vision Model to detect PCB components. By leveraging Python libraries like YOLOv10, OpenCV, PyTorch, Keras, TensorFlow, and Pandas, he significantly improved the efficiency of hardware assessments in cybersecurity. His model recognized components by their unique shapes and identifiers, reducing the time spent by engineers on manual detection tasks. Additionally, Jimmy contributed to the development of neural-based decompilers using Graph Neural Networks (GNNs). Inspired by Meta's N-Bref, his work on reverse engineering involved converting assembly language files into high-level C code, a critical process for cybersecurity and reverse engineering.

These experiences, coupled with his academic background and hands-on expertise, solidify Jimmy’s standing as an emerging talent in the field of Machine Learning and Artificial Intelligence, with a particular focus on sustainable, scalable solutions and innovative reverse engineering methods.