Very Short version
Roman Klinger is professor at the University of Stuttgart. His goal is to enable computers to understand language both regarding factual and non-factual information. The methods that he and his team develop help to automatically understanding biomedical scientific text and social media, literature, or news paper articles.
Roman Klinger is a professor at the Institute for Natural Language Processing (IMS) at the University of Stuttgart. He studied computer science with a minor in psychology, holds a Ph.D. in computer science from TU Dortmund University (2011), and received the venia legendi in computer science in Stuttgart (2020). Before moving to Stuttgart, he worked at the University of Bielefeld, at the Fraunhofer Institute for Algorithms and Scientific Computing, and the University of Massachusetts Amherst. Roman Klinger’s vision is to enable computers to understand and generate text regarding both factual and non-factual information. This finds application in interdisciplinary research, including biomedical text mining, digital humanities, modelling psychological concepts (like emotions) in language, and social media mining. These topics often constitute novel challenges to existing machine learning methods. Therefore, he and his group also contribute to the fields of probabilistic and deep machine learning.
Roman Klinger is a professor at the Institute for Natural Language Processing (IMS) at the University of Stuttgart, where he also habilitated in computer science with a thesis on modelling affect in text. He holds a Diploma (M.Sc. equivalent) in Computer Science (with a minor in Psychology), a Ph.D. in computer science (“Dr. rer. nat”), both from the TU Dortmund. Previous affiliations include the University of Bielefeld and the Fraunhofer Institute for Algorithms and Scientific Computing. Research stays and visits brought him to the information extraction and synthesis laboratory at the University of Massachusetts Amherst, headed by Prof. Andrew McCallum and the Institute for Linguistics at the University of Malta. In 2015, he cofounded the Semalytix GmbH (exit in 2020).
Roman Klinger’s research focus is nowadays the modelling of psychological concepts in text, with applications to emotion analysis and argument mining. The developed methods find application in a variety of domains, including social media, news, scientific texts and others, for the benefit of applications and interdisciplinary research spanning from bioinformatics to computational social sciences, digital humanities as well as methodological contributions to machine learning, particularly probabilistic approaches and structured learning.