Fanny Chevalier is affiliated with the University of Toronto in Canada and has contributed extensively to the field of Computer Science, with a particular focus on subfields such as Computer Vision and Pattern Recognition, Artificial Intelligence, and Human-Computer Interaction. Their research spans several topics, prominently Data Visualization and Analytics, Video Analysis and Summarization, and Machine Learning in Healthcare, among others.
Chevalier's recent publications reflect a concentration on visualization, interaction, and data presentation in computing contexts. Notable papers include "Data Comics for Reporting Controlled User Studies in Human-Computer Interaction" (2020) published in IEEE Transactions on Visualization and Computer Graphics, "Interactive Data Comics" (2021) also in IEEE Transactions on Visualization and Computer Graphics, "A Survey of Tasks and Visualizations in Multiverse Analysis Reports" (2022) in Computer Graphics Forum, "Get To The Point! Problem-Based Curated Data Views To Augment Care For Critically Ill Patients" (2022) presented at the CHI Conference on Human Factors in Computing Systems, and "Computational skills by stealth in introductory data science teaching" (2021) in Teaching Statistics.
Frequent coauthors in Chevalier's work include Benjamin Bach, Yvonne Jansen, Zezhong Wang, Minfan Zhang, and Mjaye Mazwi, with multiple collaborations recorded. This highlights a collaborative research network emphasizing both visualization and interaction in data-centric studies.
Their work has been disseminated across several publication venues, indicating a broad engagement with both theoretical and applied research communities. Key venues where Chevalier's work appears most often include:
Chevalier's research areas can be detailed further by the primary topics they cover, such as:
The scientist's work reflects a consistent focus on improving methods for presenting and interacting with complex data, often incorporating elements of human-computer interaction and advanced analytics. This multifaceted research aligns with current trends in enhancing data accessibility and usability across various domains.
A. Bezerianos;F. Chevalier;P. Dragicevic;N. Elmqvist
Tomer Moscovich;Fanny Chevalier;Nathalie Henry;Emmanuel Pietriga
Nikola Banovic;Tofi Buzali;Fanny Chevalier;Jennifer Mankoff
Basak Alper;Nathalie Henry Riche;Fanny Chevalier;Jeremy Boy
Jian Zhao;Christopher Collins;Fanny Chevalier;Ravin Balakrishnan
Rubaiat Habib Kazi;Fanny Chevalier;Tovi Grossman;Shengdong Zhao
Jian Zhao;F. Chevalier;E. Pietriga;R. Balakrishnan
Rubaiat Habib Kazi;Fanny Chevalier;Tovi Grossman;George Fitzmaurice
Pierre Dragicevic;Yvonne Jansen;Abhraneel Sarma;Matthew Kay
Fanny Chevalier;Nathalie Henry Riche;Catherine Plaisant;Amira Chalbi
Fanny Chevalier;Pierre Dragicevic;Anastasia Bezerianos;Jean-Daniel Fekete
Jian Zhao;Fanny Chevalier;Ravin Balakrishnan
Fanny Chevalier;Pierre Dragicevic;Steven Franconeri
Jian Zhao;F. Chevalier;C. Collins;R. Balakrishnan
Unknown
Pierre Dragicevic;Fanny Chevalier;Stephane Huot
Jian Zhao;Michael Glueck;Petra Isenberg;Fanny Chevalier
Rorik Henrikson;Bruno Araujo;Fanny Chevalier;Karan Singh
F. Chevalier;J. P. Domenger;J. Benois-Pineau;M. Delest
Fanny Chevalier;Nathalie Henry Riche;Basak Alper;Catherine Plaisant
Nicole Sultanum;Fanny Chevalier;Zoya Bylinskii;Zhicheng Liu
Haijun Xia;Nathalie Henry Riche;Fanny Chevalier;Bruno De Araujo
Fanny Chevalier;Romain Vuillemot;Guia Gali
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French Institute for Research in Computer Science and Automation - INRIA
Publications: 19
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