About me

I am currently an independent group leader at the MPI for Intelligent Systems in Tübingen, and will join Saarland University as a full professor in Spring 2020.

I have held a German Humboldt Post-Doctoral Fellowship, and a “Minerva fast track” fellowship from the Max Planck Society. I obtained my PhD in 2014 and MSc degree in 2012 from the University Carlos III in Madrid (Spain), and worked as postdoctoral researcher at the MPI for Software Systems (Germany) and at the University of Cambridge (UK).

Research interests

My research focuses on developing machine learning methods that are flexible, robust, interpretable and fair. Flexible means they are capable of modeling complex real-world data, which are often heterogeneous in nature and present temporal dependencies. Secondly, I aim to improve the robustness of machine learning algorithms to outliers, missing data and mixed statistical data types. Finally, I work on making algorithms fairer and interpretable – if they are part of important decision-making processes, the outcomes should be fair and explainable.

My research can be applied in a broad range of fields, from medicine and psychiatry to social and communication systems. Recently, I also began putting a special focus on consequential decision making in several domains, including hiring processes, pre-trial bail, or loan approval.

Work opportunities

I am always looking for oustanding phd students and postdocs interested to work on developing novel and efficient machine learning methods for real-world problems!