I am a Senior Software Engineer at Amazon's Alexa AI, where I focus on machine learning engineering. Specifically, I am a technical lead for developing scalable and reliable C++ and Python software for mission-critical natural language understanding models.
My primary interest in software development is to enable and augment human expression, be it through design, story telling, or other ways to connect with others.
I am a strong advocate of inclusive and accessible human-entered computing. I view computer science as a field that extends beyond algorithms alone.
Before joining the software industry, I completed a Computer Science PhD as a National Science Foundation Graduate Research Fellow at Brown University. My dissertation focused on visualization design, and drew on a variety of research methods: my work involved not just software development, but also both quantitative and qualitative human subject evaluation. Although I am now an SDE, I still have a strong UXR perspective.
While in academia, I focused on information visualization design techniques and theory. My research led to eleven publications, and also additional conference posters. For a publication list, please see my Google Scholar or dblp profiles.
Much of my dissertation focuses on color's role in effective visualization. My talk at OpenVisConf 2017, Empowering Effective Visualization (Color) Design, highlights:
- Colorgorical: an automated tool to make categorical color palettes, taking both legibility and aesthetic preference into account.
- Chromaticity: a manual color palette generation tool based on a color picker that spans a variety of perceptual color spaces, and provides warnings about ineffective color combinations.
- d3-cam02: a D3.js module that defines CIECAM02 and CIECAM02-UCS perceptual color spaces.
- d3-jnd: 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.
Aside from research on color, I also spent time looking at how information retrieval techniques can help aid qualitative evaluation of visualization design, effective design for genome visualization, as well as other areas like software visualization and crowdsourcing.