Scientific Advisory Board

Research areas | NLP, Computational Social Science, XAI

Stephanie Brandl is an Assistant Professor at the Center for Social Data Science, University of Copenhagen, specializing in Natural Language Processing. Her research focuses on human-centered explainability in NLP and politicalNLP, i.e., the intersection of Political Science with NLP. Stephanie has contributed to numerous publications and collaborations in the field of Natural Language Processing.

Research Areas | LLM in medicine, AI applications in Radiology

Keno Bressem is serving as Full Professor of Medical Data Sciences in Oncology at the German Cancer Research Center (DKFZ, NCT West) and the University of Duisburg-Essen based at the Institute for Artificial Intelligence in Medicine (IKIM). He is also a Principal Investigator at TUM University Hospital. His research focuses on natural language processing and computer vision for medical data. Keno graduated from Charité University Medical School, Berlin, in 2016, where he also earned his MD („Dr. med.“) and a university teaching qualification („Privatdozent“). After spending one year at the AI in Medicine Program at Harvard Medical School, he joined the Department of Radiology at TU Munich, German Heart Center, as Oberarzt for cardiovascular radiology. Since 2025, he has been a clinician scientist funded by the Else Kröner Excellence Fellowship (Exzellenzstipendium).

Research areas | Data Quality, Data Cleaning, Machine Learning in Data Bases

Ziawasch Abedjan is a full professor of computer science and chair of the Data Integration and Data Preparation Group at Technische Universität Berlin and the BIFOLD center of excellence. His research focuses on developing scalable, machine learning-based techniques for data integration, cleaning, and preparation. Abedjan is recognized for his contributions to data science, analytics, and databases, with numerous influential publications and collaborations in the field.

Research areas |

Patrick van der Smagt is Head of AI & Engineering at Foundation Future Industries. He has led machine learning and robotics research across academia and industry, including directing AI research at Volkswagen Group and as professor for ML and robotics at TUM. His research spans probabilistic deep learning and inference for dynamical systems, optimal control, and robotics. He is affiliated with the LMU Graduate School of Systemic Neurosciences and serves as a professor at ELTE University Budapest. He is an ELLIS, ELIAS, and ELIZA fellow, and member of the Bavarian AI Council.