In my research I focus on semantic processing of unstructured data. In recent projects I have been using machine learning and natural language processing to improve the performance of existing legal knowledge and information retrieval systems. I have extensive experience with text categorization and transformation of unstructured data into a structured representation (network, relational database). I have worked on knowledge re-use techniques for automatic classification of legal texts applying concepts from transfer learning. I have also experimented with an interactive machine learning to support legal text analysis (best student paper award at JURIX 2015 international conference). During my studies I focused on machine learning, natural language processing, cognitive computing, recommendation systems, and data visualization. I also have a law degree and fairly good understanding of European copyright, IT Law, and legal practice in general.