Christian Wagner’s research focuses on modeling & handling of uncertain data arising both from qualitative (people) and quantitative sources (e.g., sensors, process), decision support systems and data-driven policy design. He has published more than 80 peer-reviewed articles, including prize-winning papers in international journals and conferences, most recently being awarded runners-up for both the best regular and best student papers at the IEEE International Conference on Fuzzy Systems 2016 in Vancouver, Canada. He has attracted around £1 million as principal and £6 million as co-investigator in the last six years. He is an Associate Editor of the IEEE Transactions on Fuzzy Systems journal and is actively involved in the academic community through for example the organization of special sessions and tutorials at premiere IEEE conference. He has developed and been involved in the creation of multiple open source software frameworks, making cutting edge research accessible both to peer researchers as well as to different research communities beyond computer science, including an R toolkit for type-2 fuzzy systems and a new Java based framework for the object oriented implementation of general type-2 fuzzy sets and systems. His current research projects focus on the development, adaptation, deployment and evaluation of artificial intelligence techniques in inter-disciplinary projects bringing together heterogeneous data from stakeholders and quantitative measurements to support informed and transparent decision making.