Mohammad Labeeb

Intern @IAV GmbH

Heimsheim, DE

Working on research in advanced neural architectures for Autonomous Driving systems, focusing on improving Adaptive Cruise Control (ACC) through deep learning approaches- Developed and implemented transformer-based models, achieving 20% accuracy improvement and 30% latency reduction compared to traditional approaches- Enhanced LSTM neural networks for ACC applications, resulting in 30% smoother acceleration profiles in complex driving scenarios- Built end-to-end machine learning pipelines using TensorFlow, Keras, and Optuna for model optimization- Currently conducting research comparing LSTM-RNN and Transformer architectures for autonomous driving applications.