The scientist’s investigation covers issues in Visualization, Eye tracking, Artificial intelligence, Data visualization and Human–computer interaction. His Visualization research is multidisciplinary, incorporating perspectives in Sequence and Theoretical computer science. His research investigates the connection between Eye tracking and topics such as Visual analytics that intersect with issues in Field and Psychological research.
Michael Burch has included themes like Tree and Computer vision in his Artificial intelligence study. In his study, which falls under the umbrella issue of Data visualization, Computer graphics, Multiple edges, Graphics and Vertex is strongly linked to Graph theory. The Human–computer interaction study which covers Information visualization that intersects with State.
Michael Burch mainly investigates Visualization, Eye tracking, Artificial intelligence, Theoretical computer science and Data visualization. His Visualization study integrates concerns from other disciplines, such as Software visualization and Human–computer interaction. His study looks at the intersection of Eye tracking and topics like Visual analytics with Analytics.
His Artificial intelligence study incorporates themes from Computer vision and Pattern recognition. His Theoretical computer science research includes elements of Scalability, Graph drawing and Null graph. In Data visualization, Michael Burch works on issues like Tree, which are connected to Pixel and Timeline.
His scientific interests lie mostly in Visualization, Eye tracking, Information visualization, Artificial intelligence and Eye movement. He combines subjects such as Test, Hierarchical database model and Scalability with his study of Visualization. His Eye tracking research is multidisciplinary, incorporating elements of Web application, Field and Human–computer interaction.
His Information visualization study combines topics from a wide range of disciplines, such as Visual analytics, Data visualization and Interactive visualization. He has researched Artificial intelligence in several fields, including Computer vision and Pattern recognition. While the research belongs to areas of Eye movement, he spends his time largely on the problem of Visual search, intersecting his research to questions surrounding Directed graph and Graph Layout.
Michael Burch spends much of his time researching Visualization, Information visualization, Eye tracking, Visual analytics and Eye movement. Particularly relevant to Data visualization is his body of work in Visualization. His studies in Information visualization integrate themes in fields like Hierarchical database model and Layout algorithm.
In his research on the topic of Eye tracking, Analytics, Web page and Dynamic web page is strongly related with Human–computer interaction. His Visual analytics study also includes
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
State-of-the-Art of Visualization for Eye Tracking Data
Tanja Blascheck;Kuno Kurzhals;Michael Raschke;Michael Burch.
EuroVis (STARs) (2014)
A Taxonomy and Survey of Dynamic Graph Visualization
Fabian Beck;Michael Burch;Stephan Diehl;Daniel Weiskopf.
Computer Graphics Forum (2017)
The State of the Art in Visualizing Dynamic Graphs
Fabian Beck;Michael Burch;Stephan Diehl;Daniel Weiskopf.
EuroVis (STARs) (2014)
Visual Analytics Methodology for Eye Movement Studies
G. Andrienko;N. Andrienko;M. Burch;D. Weiskopf.
IEEE Transactions on Visualization and Computer Graphics (2012)
Visualization of Eye Tracking Data: A Taxonomy and Survey
Tanja Blascheck;Kuno Kurzhals;Michael Raschke;Michael Burch.
Computer Graphics Forum (2017)
Parallel Edge Splatting for Scalable Dynamic Graph Visualization
M. Burch;C. Vehlow;F. Beck;S. Diehl.
IEEE Transactions on Visualization and Computer Graphics (2011)
Evaluation of Traditional, Orthogonal, and Radial Tree Diagrams by an Eye Tracking Study
M. Burch;N. Konevtsova;J. Heinrich;M. Hoeferlin.
IEEE Transactions on Visualization and Computer Graphics (2011)
Timeradartrees: visualizing dynamic compound digraphs
M. Burch;S. Diehl.
ieee vgtc conference on visualization (2008)
User performance and reading strategies for metro maps: An eye tracking study
Rudolf Netzel;Bettina Ohlhausen;Kuno Kurzhals;Robin Woods.
Spatial Cognition and Computation (2017)
Visualizing the evolution of compound digraphs with TimeArcTrees
Martin Greilich;Michael Burch;Stephan Diehl.
ieee vgtc conference on visualization (2009)
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