Maneesh agrawala biography

Membership Add photo. Awards Add photo. Other Photos Add photo. Connections Add photo. Add photo. View map. Tools Tools. Download as PDF Printable version. In other projects. Wikidata item. American computer scientist born Life and work [ edit ]. References [ edit ]. Retrieved 7 August Silver Chips Online. Retrieved 18 October AriettaAlexei A.

Cohen Graphics Interface, May O'SheaMartin S. DruckerManeesh Agrawala and Michael F. Ink Normalization and Beautification Patrice Y. Rendering from Compressed Textures Andrew C. Beers and Navin Chaddha Proc.

Maneesh agrawala biography

ACM Multimedia, Nov We then adjust the template mappings to depict the source data by matching the most important data fields to the most perceptually effective mappings. We show how the style templates can be applied to source data in the form of either a data table or another D3 chart. While our implementation focuses on generating templates for basic chart types e.

Users can easily find such basic D3 charts on the Web, turn them into templates, and immediately see how their own data would look in the visual style e. We demonstrate the effectiveness of our approach by applying a diverse set of style templates to a variety of source datasets. Treemaps are space-filling visualizations that make efficient use of limited display space to depict large amounts of hierarchical data.

Creating perceptually effective treemaps requires carefully managing a number of design parameters including the aspect ratio and luminance of rectangles. Moreover, treemaps encode values using area, which has been found to be less accurate than judgments of other visual encodings, such as length. We conduct a series of controlled experiments aimed at producing a set of design guidelines for creating effective rectangular treemaps.

We find no evidence that luminance affects area judgments, but observe that aspect ratio does have an effect. Specifically, we find that the accuracy of area comparisons suffers when the compared rectangles have extreme aspect ratios or when both are squares. Contrary to common assumptions, the optimal distribution of rectangle aspect ratios within a treemap should include non-squares, but should avoid extremes.

We then compare treemaps with hierarchical bar chart displays to identify the data densities at which length-encoded bar charts become less effective than area-encoded treemaps. We report the transition points at which treemaps exhibit judgment accuracy on par with bar charts for both leaf and non-leaf tree nodes.