Latest Work

SenseMate: An AI-based Platform to Support Qualitative Coding

Many community organizations want to engage in conversations with their constituents but lack the support they need to analyze feedback through qualitative data analysis (QDA), or sensemaking. As a result, it’s important to provide accessible entry points into the analysis process for people with no prior experience. For my master's thesis, I’m designing SenseMate, an AI-based platform to support non-researchers in qualitative coding. After developing a codebook, or a list of themes, from a subset of the data, qualitative coding involves applying the codebook to all the data. SenseMate aims to transparently recommend themes for pieces of text to increase the efficiency and reliability of qualitative coding.

This is an ongoing project!

Future CMS Schools

I collaborated with an amazing team of people from CCC and Charlotte-Mecklenburg Schools (CMS) to create a new form of community engagement around two magnet schools opening in the fall of 2023. Through facilitated small-group conversations and various online platforms that we designed, we were able to more deeply engage CMS’ parents, students, and other community members in dialogue around their hopes and concerns for the new schools.

Personal Reminiscence Detection

For my Natural Language Processing (NLP) final project, I worked with three classmates to detect personal reminiscence from face-to-face, small-group conversation transcripts. Our NLP task was to classify whether a conversation excerpt contains an instance of personal reminiscence or not. We constructed an annotated dataset for personal reminiscence detection and implemented a variety of models for classification.

Publications and Presentations

Awards and Fellowships