Hello! I'm Rayen Dhahri, a Machine Learning Research Engineer specializing in Neural Network Optimization, Large Language Models (LLMs), and Efficient Learning. I have extensive experience optimizing and deploying complex AI models on resource-constrained devices, with a proven track record in both research and industrial settings.
With a strong academic foundation from the Technical University of Munich (TUM) and my visiting opportunities at EPFL and ETH Zurich, I have had the privilege of working with leading organizations such as Intel, Huawei, CARIAD, and BMW. I am currently working as a Machine Learning Research Engineer at the Corporate Research Team of Zeiss, doing what I love doing most (Applied Research). My work focuses on making neural networks more efficient through techniques like model sparsification, quantization, and knowledge distillation, publishing impactful research at top conferences like NeurIPS.
Recent Highlights
- š Published at NeurIPS 2024: Shaving Weights with Occam's Razor: Bayesian Sparsification for Neural Networks.
- š” LLM Optimization Expert: Extensive experience optimizing and deploying large language models on edge devices through sparsification and quantization techniques.
- š» Optimized and deployed neural networks for edge devices during my work at Intel, Huawei, BMW, and Infineon Technologies.
Get in Touch
Iām always excited to collaborate on innovative AI solutions or discuss groundbreaking research. Feel free to reach out!
- š§ Email: rayendhahri@gmail.com
- š» GitHub: Heatdh
- š LinkedIn: Rayen Dhahri