I research data visualization as a computer science PhD canditate and a NSF graduate research fellow at Brown University, where I am advised by David Laidlaw. My dissertation committee members are Jeff Huang, Ben Raphael, and Karen Schloss.
My research focuses on human-centered visualization design. Specifically, my thesis expands our understanding of effective design practices and provides new computational techniques to improve visualization stylization and task requirement analysis by working in cancer genomics application areas.
I'm currently looking for jobs starting post-academic year.
d3-cam02 is an extension to D3.js to support CIECAM02 perceptual color space, which is a modern successor to CIELAB. Supporting perceptual color spaces is critical given that interpolating in non-perceptual spaces like RGB can create perceptually misleading color shifts.
Colorgorical is a web-based tool for creating information visualization color palettes. Users design palettes by controlling the relative importance of color preference and discriminablity. Color selection can be further customized with hue and lightness filters, and users can also specify palettes to build upon.
In this work I tested how the layout, number, and physical size of data affects visualization search performance. Our findings show that perceptual grouping greatly affects performance and that performance gains from increased physical size eventually plateau.
Exploring visualization design spaces
In this work I helped code visualizations to construct a phylogenetic classification of the visualization layout design space, helped develop initial prototypes, and helped evaluate the effectiveness of our technique.
MAGI is an online cancer genomics visualization tool, which allows researchers to query sets of genes and renders mutation information across five separate views to support a myriad of analytical tasks.
GD3 is cancer genomics visualization library designed to make it easier to make interactive cancer visualizations. Built on top of D3, GD3 simplifies design by allowing users to declaratively style visualizations with JSONs. More complex stylization (e.g., global color configuration and brushing) is handled through simple dispatch configuration
Molli / TuftsViewer
Molli is a protein visualization tool that was built to support comparative structural analysis. In addition to rendering 3D structure, Molli also shows aligned sequences and residue information for each of the displayed proteins
In this study I helped test and categorize novice crowdsourcing requester strategies while also collecting faculty information about the top 50 computer science departments in the USA.
Heapviz is a visualization tool to explore snapshots of the Java heap captured during runtime. I helped create the visualization interface, which shows simplified Java heap information so that otherwise sprawling Java heaps are simplified so that data structures are recognizable.
I’m currently a computer science PhD candidate and NSF graduate research fellow at Brown University.
Before, I graduated from Tufts with a B.S. in computer science. I also minored in religion and drummed, danced, and sang in Kiniwe – Tufts’ Ghanaian performance ensemble – for four years, which was then directed by Professors Nani Agbeli (now at CalArt) and David Locke.
In college I got hooked on learning about and experiencing other cultures. Since then, I've been lucky enough to be able to visit and explore several countries first-hand. My favorite way to travel is with nothing more than a carry-on backpack.