Assistant Professor of Data Science investigating accessibility and data interaction. Previously: PhD from CMU, data interaction R&D at Adobe, Highsoft, Apple, Visa, + others.
My final research project looked at the barriers that sighted practitioners face when authoring non-visual data experiences. We co-designed, built tooling, built a UI prototype, and ran a study.
The journey towards a PhD has at least three possible endings, any of which are worth celebrating. I'll unpack those.
It is completely acceptable to reject modern AI entirely on selfish grounds. Here I offer a 3-part mini-manifesto focused on why, entirely for yourself, you should consider rejecting generative AI.
(Think of this as a small experiment of sorts.)
Have you ever seen a real-life wizard battle? 🧙🏻♂️
I keep hearing folks claim that the fact we can 'prototype' so quickly now is a good thing (thanks to modern genAI). But what if the slow parts about prototyping are actually what make it worth doing?
Announcing: I've accepted a tenure-track research and teaching faculty position! But here's why R1s weren't a priority for me this job cycle.
Advice I would have given to my past self, who was graduating college.
In collaboration with Alberto Cairo's Open Visualization Academy, I have released a full course on accessibility in visualization.
My most adventurous year yet. This year, without any doubt, I know that the PhD was worth it.