Machine Learning

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In a broad perspective, my main research ambition is to understand the fundamental computational principles of learning that characterize intelligence. More specifically, my research interests are focussed on the development, analysis, and application of deep learning models and methods. I am particularly interested in analysing and developing probabilistic models and inference methods, investigating biologically plausible deep learning, and understanding the stochastic processes involved in the training and optimisation of neural networks and probabilistic models.

Before becoming a professor in Bochum I was an assistant professor at RUB, akademische Rätin (assistant professor) at Bonn university, and a post-doctoral researcher at the Montreal Institute for Learning Algorithms (MILA). Between 2010 and 2015, I was employed both at the Institute for Neural Computation at the Ruhr-University Bochum and the Department of Computer Science at the University of Copenhagen working on my PhD, which I defended in Copenhagen in 2014. Before, I studied Biology. Bioinformatics, Mathematics, and Cognitive Science at the Ruhr-University Bochum, the Universidade de Lisboa, and the University of Osnabrück.