Dipl.-Ing. Kavin Chandrasekaran

Machine Learning and Sensor Fusion: • Work with and adapt state-of-the-art deep convolutional neural network architectures for computer vision tasks, focusing on performance evaluation and improvement. • Preprocess and structure multi-modal data (camera, radar, LiDAR) to support efficient sensor fusion and downstream model performance. • Support intellectual property activities and generate invention disclosure memos to facilitate patent applications.

• Develop CNN-based perception algorithms for object classification and semantic segmentation while supporting the development of safety-critical autonomous driving systems. • Organize and preprocess multi-modal sensor data and support the development of scalable neural network training infrastructure. • Evaluate AI models across diverse datasets, driving scenarios, and environmental conditions to validate performance, robustness, and identify potential failure modes.

Vehicle dynamics and autonomous driving department: • Lateral velocity estimation using extended Kalman filter in MATLAB/SIMULINK. • Ensure high quality, relevant, and properly structured data that meets the customer requirements.