Dr.-Ing. Christoph Kinkeldey
From June to December 2020, Christoph Kinkeldey was a postdoctoral Research Associate at the Cluster in the field of visualization, leveraging knowledge and principles from cartography for interactive visual data analysis and interpretable machine learning. His main research interest is how visual communication of uncertainty can support people to gain a better understanding of complex information.
Christoph received his PhD (Dr.-Ing.) in Geoinformatics from HafenCity University Hamburg in 2015. With his academic and professional background in uncertainty visualization, visual analytics, and geovisualization, Christoph has been conducting research at institutions in the US (PennState University), Australia (University of Melbourne), France (Inria), and Germany (Freie Universität Berlin, HafenCity University Hamburg).
Articles
Benjamin, J. J., Kinkeldey, C., Müller-Birn, C. 2020. »Participatory Design of a Machine Learning Driven Visualization System for Non-Technical Stakeholders.« Mensch und Computer 2020-Workshopband, https://dl.gi.de/bitstream/handle/20.500.12116/33538/muc2020-ws-287.pdf?sequence=1&isAllowed=y
Kinkeldey, C., Müller-Birn, C., Gülenman, T., Benjamin, J. J., Halfaker, A. 2019. »PreCall: A Visual Interface for Threshold Optimization in ML Model Selection.« arXiv, https://arxiv.org/pdf/1907.05131.pdf
Others
Benjamin, J. J., Müller-Birn, C., Kinkeldey, C. 2019. Understanding Knowledge Transfer Activities at a Research Institution through Semi-Structured Interviews. Technical Report, Freie Universität Universität, Fachbereich Mathematik und Informatik. Berlin: Freie Universität Berlin. https://doi.org/10.17169/refubium-3970
Korjakow, T., Benjamin, J. J., Kinkeldey, C., Müller-Birn, C. 2019. Literature Mapping Study for Machine Learning Interpretability Techniques. Technical Report, Freie Universität Universität, Fachbereich Mathematik und Informatik. Berlin: Freie Universität Berlin. https://osf.io/t4q9s/download