I am an SDE3 (i.e., Senior SDE) at Amazon, where I specialize in machine learning and data-intensive software. I currently work within Amazon Pharmacy (PillPack). Previously I worked in Alexa AI, where I was the technical lead for developing scalable and reliable C++ and Python software for mission-critical natural language understanding models.
I take a human-computer interaction view of computer science; Computer science is more than just the code we write and the algorithms we design.
Previously, I completed a Computer Science PhD as a National Science Foundation Graduate Research Fellow at Brown University. My dissertation focused on visualization design, and I leveraged a wide array of research methods (e.g., systems work, aglorithm design, and human subject evaluation).
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Amazon, Boston and Cambridge, MA, 2017 – Present
- Amazon Pharmacy, Senior Software Development Engineer / SDE3, 2021 – Present
- Alexa AI, Senior Software Development Engineer / SDE3, 2021
- Alexa AI, Software Development Engineer, 2018 - 2021
- Audible on Alexa, Software Development Engineer, 2017 – 2018
Google, Cambridge, MA. Software Engineer Intern. 2012.
Charles River Analytics, Cambridge, MA. Software Engineer Intern. 2011.
Brown University, Providence, RI. Graduate Researcher. 2012-2017.
Tufts University, Somerville, MA. Undergraduate Researcher & TA. 2008-2012.
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 Semantic Scholar, 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.