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Supporting Human Expertise in Data Analytics with Collaborative Visualization Methods and Tools

PhD defence, Wednesday 14 August 2019. Andreas Mathisen.

2019.08.14 | Maia Høyer Monod

Andreas Mathisen

During his studies, Andreas has researched on how to design visualization-based technologies that can better support collaboration and performance of data analysis in organisational contexts. Through studies in companies and public institutions, he found that utilization of existing knowledge capital and mixed expertise collaboration are central aspects in successfully deriving value from data. Among Andreas’ results are visual analysis methods and tools for temporal event sequence data that can e.g. be used to identify suspicious company behaviour in governmental service, or to reason about treatment pathways in healthcare. Andreas has also developed collaboration technologies that allow collaborators to share computational analysis methods as well as to communicate analytical findings with full transparency. The novel visualization-based methods and technologies contribute to the understanding of how to support humans in utilizing data in real world domains. Andreas’ results both contribute to enrich the human processes in the early exploratory phases of data analysis as well as in explaining results of underlying automatic analysis algorithms to users.

The PhD degree was completed at the Department of Computer Science, Science and Technology, Aarhus University.

This résumé was prepared by the PhD student.

Time: Wednesday 14 August 2019 at 10:00
Place: Building 5342, room 333, Ada-333, Department of Computer Science, Aarhus University, Åbogade 34, 8200 Aarhus N
Title of PhD thesis: Collaborative Visual Analytics – Leveraging Mixed Expertise in Data Analysis
Contact information: Andreas Mathisen, e-mail: am@cs.au.dk 
Members of the assessment committee:
Professor Jason Dykes, Department of Computer Science, City University London, United Kingdom
Professor Sheelagh Carpendale, Department of Computer Science, University of Calgary, Canada
Professor Anders Møller, Department of Computer Science, Aarhus University (chair)
Main supervisor:
Professor Kaj Grønbæk, Department of Computer Science, Aarhus University
Language: The PhD dissertation will be defended in English

The defence is public.
The PhD thesis is available for reading at the Graduate School of Science and Technology/GSST, Ny Munkegade 120, building 1521, 8000 Aarhus C.

PhD defence
12183 / i43