Thesis in progress
Group : Human-Centered Computing

La théorie de l’information comme un outil unifié pour comprendre et concevoir l’interaction humain-machine

Starts on 01/11/2015
Advisor : BEAUDOUIN-LAFON, Michel

Funding :
Affiliation : vide
Laboratory : LRI et Télécom Paris Tech

Defended on 22/11/2018, committee :

Research activities :

Abstract :
Information theory has influenced a large number of scientific fields since its first introduction in 1948. Apart from Fitts' law and Hick's law, which came out when experimental psychologists were still enthusiastic about applying information theory to various areas of psychology, the relation between information theory and human-computer interaction (HCI) has rarely been explored. This thesis strives to bridge the gap between information theory and HCI by taking the stance that human-computer interaction can be considered as a communication process and therefore can be characterized using information-theoretic concepts. The three main contributions are: (1) a detailed historical perspective on how information theory influenced psychology and HCI, particularly an in-depth discussion and analysis of how relevant Hick's law is to HCI; (2) a Bayesian Information Gain (BIG) framework that quantifies the information sent by the user to the computer to express her intention; and (3) a further illustration of the advantages of using information-theoretic measures to evaluate input performance and to characterize the rich aspects of an interaction task. This thesis demonstrates that information theory can be used as a unified tool to understand and design human-computer communication.

CAUSAL LEARNING FOR DIAGNOSTIC SUPPORT


CAUSAL UNCERTAINTY QUANTIFICATION UNDER PARTIAL KNOWLEDGE AND LOW DATA REGIMES


MICRO VISUALIZATIONS: DESIGN AND ANALYSIS OF VISUALIZATIONS FOR SMALL DISPLAY SPACES
The 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.