Assistant Professor in Computer Science and Statistics
University of Toronto
Fanny Chevalier is an Assistant Professor in Computer Science and Statistics at the University of Toronto, since 2018. Prior to that, she was a research scientist at Inria, France. She obtained her PhD in computer science from the Université de Bordeaux, in 2007.
Her research interests lie in Human-Computer Interaction and Information Visualization in the broad sense. More specifically, she is interested in addressing the challenges involved in the design, implementation, and evaluation of novel interactive tools supporting visual analytics and creative activities, with primary focus on interactive visualization for the visual exploration of rich and complex data, visualization education, computing tools supporting the flow of creativity, the design and perception of animated transitions, and sketch-based interfaces.
She has published over 60 articles in the top venues in the areas of Human-Computer Interaction (ACM CHI, ACM UIST) and Visualization (IEEE Infovis, IEEE VAST, IEEE TVCG), several of which received nominations and awards for best paper. Her work at the intersection of visualization and creativity has led to technologies that are now in commercial products, such as Autodesk Sketchbook Motion, selected as Apple’s 2016 iPad App of the Year. She has also consistently served in both the organizing and technical program committees for the top-tier venues of her field for the past decade. She is the IEEE VIS 2019 program chair for short papers, and the upcoming program chair for the ACM UIST 2020, ACM ISS 2020 and GI 2020 conferences.
Technical Vision Talk Abstract: "Don’t look. See! Are We Blinded by Data (Visualization)?"
We are constantly required to make decisions about the world we live in. But are we good judges of how things work and what is best to do in each situation? Dr. Chevalier’s talk will explore why we may not always make well-informed decisions, even with best intentions, and even when our motivations are driven by careful examination of data. She will challenge the ways we leverage data for analysis and communication, and propose strategies that embrace the imperfect, subjective nature of human’s perception.