Biagio Licari

Researched, identified, and implemented optimal AutoML solutions for clustering and relevant frameworks. Benchmarked different AutoML solutions and evaluated their performance through comprehensive experiments Proficiently used Neptune for organized data storage, ensuring data integrity Leveraged Python to extract insights from Neptune's data, presenting clear and actionable results

• Successfully designed and implemented a state-of-the-art Local Path Planner for dynamic obstacle avoidance in an autonomous car. • Achieved outstanding performance by securing a top 3 ranking in the competitive dynamic obstacle race for self-driving vehicles. • Collaborated closely with the engineering team to define requirements and design the system architecture. Coordinated the deployment phase by integrating the Local Path Planner as a ROS node.