The growing use of digital technologies in the education system has generated large amounts of data that records educational processes at a granular level. This project aims to leverage large-scale text data and NLP and causal inference techniques to understand the interplay between instructional contexts, students’ day-to-day online communication experience, and systematic inequality in academic achievement. This understanding can help educators create a more inclusive and effective educational environment to promote engagement and sense of belonging for students from marginalized groups, thereby reducing existing inequities in the system.

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The goal of this project is to develop and mathematically analyze simple models of empirical phenomena observed in deep learning.

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The REACH OUT study is a multi-institutional collaboration funded by the Health Effects Institute to determine if populations who have been chronically exposed to higher levels of air pollution are at greater risk of severe COVID-19 outcomes. This is a paid position which will provide students with the opportunity to use analytic approaches on public health and environmental data. The selected student will work as part of a research team to analyze publicly available COVID-related and environmental data from the New York City Department of Health. They will also integrate findings with those from harmonized electronic health records and conduct simulations to assess the potential for selection bias in study populations. All analyses will be performed using R/R Studio. Students will be expected to create shareable and commented code as part of this work. Students will also create visualizations to communicate study results in publications and presentations.

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Type 1 diabetes (T1D) is a chronic autoimmune disease that requires patients to need lifelong insulin therapy. Diabetes technology (insulin pumps and continuous glucose monitors (CGM)) have been shown to reduce the risk of high and low blood sugars and thus reduce long term diabetes complications. Hybrid closed-loop (HCL) insulin pumps integrate CGM technology to automatically adjust insulin delivery from the pump, with the goal of improved blood sugar and better quality of life for the patient. There are two commonly used HCL systems in our diabetes center: the t:slim x2 with Control IQ (TS) and the Omnipod 5 (O5).

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