Already employed as a senior lecturer the appointment allows Klinger to join the faculty council and the independent supervision of doctoral students.
Klinger joined the Institute for Natural Language Processing (IMS) in 2014 and completed his habilitation at the University of Stuttgart in 2020 ("Structured Modeling of Affect in Text"). Currently, he is investigating how computers can not only understand explicitly formulated facts in texts, but also read between the lines. He clarifies his research interest as follows: "For us to talk to computers, they need to understand not only content and questions, but also assess how we feel, what our intentions are, and whether we might be telling lies."
His research focuses on emotion analysis, argument mining and fact checking, sentiment analysis, information extraction, deep learning and probabilistic machine learning models, as well as zero-shot learning and few-shot learning. In terms of methodology, Klinger and his team rely on machine learning methods based on large language models. One of their representatives is the currently omnipresent ChatGPT.
In his teaching, Klinger integrates various courses from computational linguistics, data science and computer science to digital humanities. The skills taught include information retrieval and text mining, natural language understanding, and emotion analysis.