My research is at the intersection of machine learning (ML) and human-computer interaction (HCI). I’m interested in making ML systems more grounded in context. In my current work, this takes a lot of forms: for example, co-designing context-specific datasets and models for counterdata collection, or developing tools and theory for communicating the limitations of ML systems to the people who use them and are affected by them.
Before this, I did my undergrad and M.Eng. at MIT as well, working on ML for healthcare. During my PhD, I’ve spent a couple summers interning at Google Brain, where I worked on studying biases in word embedding models and building interactive visualizations of books with sentence embeddings. I also love traveling, reading, cooking and baking, and doing aerial arts. (This website template is forked from this repo.)