Nina Hubig

Research group:

Our mission is to transform AI into a more transparent and trustworthy tool by ensuring that its decisions and actions are easily understood by everyone. As AI continues to influence all aspects of daily life—from healthcare to industry and personal environments—we aim to make these systems more accessible and less mysterious, fostering confidence in their use. By focusing on clarity and explanation, we help bridge the gap between the complexity of AI and the needs of individuals, empowering them to engage with technology in a meaningful and informed way.

Short bio:

Nina Hubig is an Assistant Professor at IT:U after five years teaching and researching at Clemson University in the School of Computing and the Biomedical Data Science Program. Her research focuses on Explainable Artificial Intelligence (XAI), particularly in the context of healthcare and data science, aiming to improve transparency in AI systems used for critical applications like medical data processing and social network analysis. She has extensive experience in machine learning, explainability, and fairness in AI, and is known for her work on integrating deep learning models into practical systems, such as those used in real-time flood detection and biomedical applications. Dr. Hubig earned her Ph.D. from the Technical University of Munich and has contributed significantly to both academic and applied AI research, mentoring projects that bridge AI with medical text processing and natural language understanding (NLP) systems.