My main work focuses on machine learning for decision making and control, with an emphasis on deep learning and semi-supervised learning algorithms. My research includes vision-based control used as advanced driver assistance systems (ADAS) in autonomous vehicles, sensory perception and control of intelligent robots, real-time machine vision and image processing, developing algorithms for deep neural network policies that combines perception and control, developing deep learning methods for object recognition and detection, and predicting the human behavior in multi-agent scenarios using algorithmic game theory and inverse reinforcement learning, to name but a few. I am interested in these areas mainly because of their interdisciplinary nature which is closely interwoven with Control and Artificial intelligence.