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Our project aims to examine whether it is feasible to build machine learning classifiers that can effectively predict an upcoming psychiatric hospitalization given social media data from platforms unseen in the classifiers' training data, despite the preliminary evidence on identity fragmentation between Facebook, Twitter, and Instagram. It also aims to explain any discrepancies in performance that are found during analysis between intra- and inter-platform classification.

Tech Hustle is a project to build upon indications from earlier project, Glitch. Glitch found that many low-income African American male high school students were more willing and able to engage in computer education when it was situated in an authentic work environments. The high school students in this previous work exhibited pride and excitement in being responsible workers, making their own money, and used work as a way to justify time spent on learning computer science and other more academic pursuits.

This project visualizes health data within the Atlanta metro region. Although some research about health inequities among this region has occurred, it typically is based on county-level data. In order to have a better understanding of health inequities and disparities in our home area, a city profile for Atlanta should be established. This project has created an interactive visualization of data such as rates of teen pregnancies, low birthweight babies, etc. The system allows the viewer to explore correlations among the different variables.