About

I am a Tenure-Track Professor of Data Science at the Faculty of Economics and Business Studies of the University of Giessen. Before joining the University of Giessen, I worked as a postdoctoral researcher in machine learning at the University of Oxford, where I remain affiliated as an Associate Member at the Oxford-Man Institute. Prior to that, I headed a research group at the University of Freiburg where I also obtained my Ph.D. in Information Systems. My research focuses on data science methods and computational techniques for understanding and predicting human decision-making in the digital age. Current research projects apply machine learning and natural language processing to a broad selection of topics, including social networks, recommender systems and financial markets. Apart from academic research, I am a passionate programmer and interested in developing novel data science methods with high business value.

Featured Research

Negation Scope Detection Using Reinforcement Learning

Negation scope detection is widely performed as a supervised learning task which relies upon negation labels at word level. This suffers from two key drawbacks: (1) such granular annotations are costly and (2) highly subjective, since, due to the absence of explicit linguistic resolution rules, human annotators often disagree in the perceived negation scopes. To the best of our knowledge, our work presents the first approach that eliminates the need for word-level negation labels, replacing it instead with document-level sentiment annotations.

Paper at NAACL-HLT 2019