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George Fitzmaurice

Director, Human Computer Interaction and Visualization Research Group

Toronto, Canada

Biography

George Fitzmaurice, Ph.D. is a Director of Research and heads the Human Computer Interaction and Visualization Research group. Collaborating with his colleagues he has co-authored and published over 120 research papers and awarded over 95 patents. During the last 25 years his research has focused on technology-assisted learning systems, knowledge capture and retrieval, highly interactive visualization systems, AR/VR and novel input and interaction techniques. Some notable research transfer and product contributions include Maya 1.0 UI, SketchBook Pro UI design, the 3D Navigation tools (ViewCube™ and SteeringWheels™), Autodesk Screencast and Sketchbook Motion (awarded Apple iPad App of the Year for 2016). Fitzmaurice received a B.Sc. in Mathematics with Computer Science at MIT, an M.Sc. in Computer Science at Brown University and a Ph.D. in Computer Science at the University of Toronto. He established the field of Graspable UIs which is the pre-cursor to Tangible UIs and pioneered the concept of spatially-aware displays and situated information spaces with the Chameleon research project. In 2019 he was inducted into the ACM CHI Academy for his substantial contributions to the field of HCI.

Publications

Related Projects

Visualization & Visual Analytics

Visual data representations leverage the power of human perception to process complex information, and through interaction, garner new insights. Our research focuses on visualizing data from a wide variety of domains and fundamentally tackles the question, what makes a visualization effective? We explore novel visual encodings and interaction techniques, multiscale approaches, and even simulation to bridge human and automated analysis of multivariate, time-series, and graph data, ultimately aiding in hypothesis generation, testing, and sense making.

Software Learning

The Learning project aims to investigate advanced techniques for assisting users in learning complicated applications. We are interested in a range of investigations from the scientific study of the human learning process to prototyping novel interaction techniques for improving the general learning mechanisms that can be applied to all applications.

CommunityCommands

Amazon recommends books to its users. Netflix recommends movies. With CommunityCommands, Autodesk will recommend command functionality to its users. CommunityCommands collects usage data from thousands of Autodesk users, through the Customer Involvement Program (CIP), and then generates personalized command recommendations using newly developed algorithms. CommunityCommands will expose users to the critical commands which they should be using, but are not aware of, accelerating the learning process.

OrgOrgChart: The Evolution of an Organization

The OrgOrgChart (Organic Organization Chart) project looks at the evolution of a company's structure over time. A snapshot of the Autodesk organizational hierarchy was taken each day between May 2007 and June 2011, a span of 1498 days.