Colorgorical

Colorgorical is a tool to make categorical visualization color palette design easier, given the frequent difficulties that arise when trying to balance aesthetics with legibility constraints. Large-scale evaluations show that palettes automatically made by Colorgorical are as discriminable and are typically more preferable compared to the defaults included in ColorBrewer, Microsoft, and Tableau. (use) (paper) (source)

full stack Javascript Python C NumPy D3.js R linear regression quantitative

d3-cam02

d3-cam02 is a D3.js module that defines CIECAM02 and CIECAM02-UCS color spaces. CIECAM02 and CIECAM02-UCS are two of the most perceptually accurate color spaces, which is particularly important for visualization design given that perceptual color differences often encode meaning. (use) (source)

Javascript D3.js

d3-jnd

d3-jnd is a D3.js module that allows designers to quickly check whether two colors can be easily differentiated, and considers how color discriminability can shift with changes in size. (use) (source)

Javascript D3.js

Exploring visualization design spaces

I created a collection of hierarchal visualization annotations and developed a prototype to explore the design space for phylogenetic design classification results. (paper)

Java qualitative

Classifying interaction behavior

I designed a new feature set based on recent eyetracking advances to classify visualization interaction behavior by mining anonymized cancer visual analysis mouse interaction logs. (under review)

Python Javascript scikit-learn D3.js MongoDB R classification inter-rater reliability quantitative

Usability requirements for cancer genomics visualization

I performed a contextual inquiry to synthesize four common cancer genomics task requirements and then evaluated whether MAGI's interface supported these needs. My analysis focused on including the full diaspora of research subdisciplines to define and evaluate usability. (under review)

requirements analysis contextual inquiry qualitative

Visualization search

I performed a series of quantitative evaluations to identify design practices based on how the layout, number, and physical size of data affects visualization search performance. (paper)

Javascript D3.js node.js R linear regression ANOVA NASA TLX quantitative

MAGI

MAGI is an online cancer genomics visualization tool, which supports visual exploration over five types of mutation data. (use) (paper) (source)

full stack Javascript D3.js node.js MongoDB

GD3

GD3 is a declarative cancer genomics visualization library built on top of D3. (source)

Javascript D3.js

Molli / TuftsViewer

Molli is a protein visualization tool that supports comparative structural analysis via 3D models, sequence alignment, and residue information. (paper) (source)

C++ OpenGL quantitative

Crowdsourcing methodology

I helped test and categorize crowdsourcing requester strategies through a computer science faculty information gathering task. (use) (paper)

crowd sourcing

Heapviz

Heapviz is a tool to help debug Java applications at runtime by visualizing summaries of Java heap snapshots. (paper)

Java Prefuse