He received his PhD in 2012 on the topic of real-time systems, but has been working on Machine Learning ever since. His current interest is Reliable Machine Learning, where the goal is to perform machine learning tasks, such as failure prediction or wear estimation, using real industrial data which is often noisy, corrupted, partially missing or coming from dynamic environments which change over time. He is interested in putting the theory in practice, which he has been doing through collaborations with industry.