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Ph.D de

Ph.D
Group : Human-Centered Computing

From data exploration to presentation: designing new systems and interaction techniques to enhance the sense-making process

Starts on 01/06/2016
Advisor : PIETRIGA, Emmanuel

Funding : Convention industrielle de formation par la recherche
Affiliation : vide
Laboratory : LRI - HCC

Defended on 03/10/2019, committee :
Directeur de thèse :
- Emmanuel Pietriga, Directeur de Recherche, Inria Saclay

Co-directeur de thèse :
- Caroline Appert, Directeur de Recherche, CNRS

Rapporteurs :
- David Auber, Professeur, Université de Bordeaux
- Daniel Wigdor, Professeur, University of Toronto

Examinateurs :
- Jean-Daniel Fekete, Directeur de Recherche, Inria Saclay
- Uta Hinrichs, Professeur, University of St Andrews
- Stephane Huot, Directeur de Recherche, Inria Lille

Research activities :

Abstract :
During the last decade, the amount of data has been constantly increasing. These data can come from several sources such as smartphones, audio recorders, cameras, sensors, simulations, and can have various structure. While computers can help us process these data, human judgment and domain expertise is what turns the data into actual knowledge. However, making sense of this increasing amount of diverse data requires visualization and interaction techniques.This thesis contributes such techniques to facilitate data exploration and presentation, during sense-making activities.

We show in this thesis that the sense-making process can be enhanced in both processes of exploration and presentation, by using ink as a new medium to transition between exploration and externalization, and by following a flexible, iterative process to create expressive data representations.The resulting systems establish a research framework where presentation and exploration are a core part of visual data systems.

Ph.D. dissertations & Faculty habilitations
DESIGNING INTERACTIVE TOOLS FOR CREATORS AND CREATIVE WORK
Creative work has been at the core of research in Human-Computer Interaction (HCI). I describe the results of a series of studies that look at how creators work, where creators include artists with years of professional practice, as well as learners, or novices and casual makers. My research focuses on three creation activities: drawing, physical modeling, and music composition. For these activities, I examine how artists switch between representations and how these representations evolve throughout their creative process, from early sketches to fine-grained forms or structured vocabularies. I present interactive systems that enrich their workflow (i) by extending their computer tools with physical user interfaces, or (ii) by making physical materials interactive. I also argue that sketch-based representations can allow for user interfaces that are more personal and less rigid. My presentation will reflect on lessons and limitations of this work and discuss challenges for future design-support tools.

INCREASING THE BANDWIDTH OF INTERACTIVE VISUALIZATIONS, USING COMPLEX DISPLAY ENVIRONMENTS AND TARGETED DESIGNS
Interactive visualizations combine human computer interaction, visual design, perception theory, as well as data processing methods in order to propose visual data representations that amplify cognition, and aid data exploration and understanding. We can consider visualization as a communication medium or channel between humans and their data. The higher the communication bandwidth (the data that can be communicated and understood), the more effective the visualization is. My research attempts to increase the bandwidth of this communication channel in the following two ways. (i) First, by moving away from traditional desktops towards larger displays that can both render larger amounts of data and can accommodate multiple viewers. (ii) And second, by designing and studying appropriate visual representations that show salient information. In my presentation I will describe my work on these topics, the challenges it tries to address, and discuss the methodology and inspiration behind this research.

MODéLISATION DE SYSTèME PHYSIQUES PAR APPRENTISSAGE STATISTIQUE PROFOND