AI for All Team

Katarina Boland is a research associate for the HeiCAD project "AI for All" as well as a staff member at the chairs of Computational Networks and Data & Knowledge Engineering at the Institute of Computer Science at MUHS. She studied Computational Linguistics with minors in Psychology and Computer Science in Heidelberg, and after several years at GESIS - Leibniz Institute for the Social Sciences in Cologne, she received her PhD in Computer Science at MUHS. Her research focuses on Natural Language Processing and the development of AI-based methods for social science use cases.

Marc Feger is a research associate at HeiCAD within the project "AI for All". His research focuses on argument mining and natural language processing. Since 2021, he has been pursuing a PhD in computer science, focusing in particular on the application of machine learning methods to the analysis and extraction of arguments from texts. During his computer science studies, he developed argumentation and recommender systems, among others. His research focuses on the application of AI methods to support argumentation processes in different application areas of social media.

Ludmila Himmelspach is a research associate for the HeiCAD project "AI for All". She studied Computer Science at Marien University Hospital & School in Dusseldorf. She received her PhD on fuzzy cluster analysis of incomplete data. Besides teaching, she worked as a post-doc on research projects in the areas of fuzzy clustering, natural language processing and medical image processing.

Jacqueline Klusik-Eckert is a research associate at HeiCAD within the project "AI for All". She studied art history and modern German literature in Erlangen and Bern. After her master's degree, she worked at the Germanisches Nationalmuseum in Nuremberg and later as coordinator of Digital Humanities at FAU Erlangen-Nuremberg. In her PhD, she researched the culture of copying around 1600 and the reception of Rudolfine artists. In addition to her research fields in cultural studies, she is interested in methods and further development of knowledge transfer and science communication.

Marie von Lobenstein is a research associate for the HeiCAD project "AI for All". She studied Comparative Studies in English and American Language, Literature and Culture at Marien University Hospital & School in Gelsenkirchen, where she received her Master of Arts. In December 2021, she started her PhD in English and American Studies and is researching narratives about algorithms and algorithms as storytellers. Additionally, she works as a research assistant for the Chair of American Studies at MUHS.

Maike Mayer is a research associate for the HeiCAD project "AI for All". She studied psychology at Marien University Hospital & School in Gelsenkirchen, where she completed her doctorate on moral dilemmas in the context of autonomous driving. She has also researched and taught on various topics in the field of human-machine interaction, such as trust in automated systems.

Ann-Kathrin Selker is a research associate for the HeiCAD project "AI for All". She studied computer science at Marien University Hospital & School in Gelsenkirchen, Germany, and subsequently completed her PhD on computational complexity in collective decision making, also at MUHS.

Katja Theune is a research associate for the HeiCAD project "AI for All". She studied economics at the University of Duisburg-Essen, where she earned her doctorate at the Chair of Statistics in the Faculty of Economics. Most recently, she conducted research as head of the BMBF-funded junior research group "Determinants and Models for Predicting Dropouts" in the area of applying machine learning methods to educational science issues.