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Ph.D de |
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Ph.D
Group : Verification of Algorithms, Languages and Systems
Formalizing Time and Causality in Polychronous Polytimed Models
Starts on 01/10/2014
Advisor : WOLFF, Burkhart
Funding : Contrat doctoral uniquement recherche
Affiliation : Université Paris-Saclay
Laboratory : LRI - VALS
Defended on 27/09/2018, committee :
Directeurs de thèse :
- Frédéric Boulanger, CentraleSupélec
- Burkhart Wolff, Université Paris-Sud
Rapporteurs :
- Frédéric Mallet, Université Nice Sophia Antipolis
- Stephan Merz, Inria Nancy
Examinateurs :
- Catherine Dubois, ENSIIE
- Timothy Bourke, Inria Paris
- Marc Pantel, Université de Toulouse
- Mihaela Sighireanu, Université Paris Diderot
Research activities :
Abstract :
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Ph.D. dissertations & Faculty habilitations |
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CAUSAL LEARNING FOR DIAGNOSTIC SUPPORTCAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMESMICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACESThe topic of this habilitation is the study of very small data visualizations, micro visualizations, in display contexts that can only dedicate minimal rendering space for data representations. For several years, together with my collaborators, I have been studying human perception, interaction, and analysis with micro visualizations in multiple contexts. In this document I bring together three of my research streams related to micro visualizations: data glyphs, where my joint research focused on studying the perception of small-multiple micro visualizations, word-scale visualizations, where my joint research focused on small visualizations embedded in text-documents, and small mobile data visualizations for smartwatches or fitness trackers. I consider these types of small visualizations together under the umbrella term ``micro visualizations.'' Micro visualizations are useful in multiple visualization contexts and I have been working towards a better understanding of the complexities involved in designing and using micro visualizations. Here, I define the term micro visualization, summarize my own and other past research and design guidelines and outline several design spaces for different types of micro visualizations based on some of the work I was involved in since my PhD.
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