Rodwan Bagdadi

- Enhanced the accuracy of AI model outputs by implementing Reinforcement Learning from Human Feedback (RLHF), achieving a remarkable 45% reduction in erroneous predictions across a dataset of over 500,000 entries. - Spearheaded the development and integration of RLHF techniques into existing AI frameworks, resulting in a 60% improvement in overall model performance metrics within just three months, directly impacting client satisfaction ratings by 35%.

- Developed and optimized AI-based algorithms that improved steering software functionality, resulting in a 30% reduction in processing time for real-time vehicle simulations using MATLAB/Simulink. - Collaborated with cross-functional teams to integrate lane keeping and automated parking functionalities into existing systems, successfully increasing system efficiency by 25%, while reducing development time by 15%.