AI Engineer for Advanced Driver-Assistance Systems (ADAS)

This AI Engineer specializes in Advanced Driver-Assistance Systems (ADAS), developing cutting-edge machine learning models that enhance vehicle safety, improve real-time object detection, and enable autonomous driving. With experience in AI-driven navigation, sensor fusion, and predictive analytics, this expert builds intelligent automotive solutions that optimize road safety and driver convenience.

• AI-Powered Collision Avoidance System – Developed a deep learning model that reduced false-positive detections by 40%, enhancing vehicle safety.
  
  Autonomous Lane-Keeping Assist – Designed an AI-driven lane detection algorithm using OpenCV and TensorFlow, improving lane-keeping precision by 35%.
  
  Real-Time Pedestrian Detection – Created an AI system with YOLO and LiDAR, increasing pedestrian detection accuracy by 50% in urban environments.
  
  ADAS Data Processing & Sensor Fusion – Developed a multi-sensor fusion model integrating radar, LiDAR, and cameras to enhance object detection capabilities.
  
  Adaptive Cruise Control (ACC) Optimization – Implemented machine learning techniques to improve adaptive cruise control efficiency by 20%, reducing energy consumption.