Fuad Ibrahimli

Statistics undergraduate with a strong interest in Data Science, Robotics, and Computer Vision. Member of the Autonomous Systems Group at METU Formula Racing, focusing on perception tasks. Experienced in Python, R, OpenCV, YOLO, sensor fusion, LIDAR, and RADAR.

• Autonomous Vehicle Perception System - Traffic sign detection pipeline using YOLOv8 with ROS integration for real-time processing
• Multi-Sensor Fusion Framework - Combined LIDAR and RADAR data streams to enhance object detection accuracy in autonomous systems
• Time Series Forecasting Platform - Built comprehensive forecasting models using ARIMA and Prophet with automated backtesting capabilities
• Real-time Object Classification - Developed CNN-based classification models optimized for embedded systems deployment