The question we ask is whether online echo-chambers on social media networks enhance the anxiety and depression of individuals during the COVID19 outbreak. More specifically we want to measure the intensity of the communication about COVID-19 within the echo-chamber of individuals on Twitter and investigate the impact on their subsequent tweets in terms of the level of anxiety and signs of depressive language in their Tweets. We measure echo-chambers by the number of users in the social network that tweeted about COVID-19. We build on an extensive dataset of Twitter users for whom we have identified a large number of demographic and geographic variables (such as the gender, age, ethnicity, location by state, political affiliation) as well as their social network.

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The objective of this project is to construct linkages across disparate public health data systems using machine learning tools and assess them for bias and equitable representation of subpopulations defined by demographic and socioeconomic factors.

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42% of New York City greenhouse gas emissions result from on-site fossil fuel combustion in residential and commercial buildings; space heating is, by far, the majority contributor. Both New York State and NYC have policies to dramatically reduce emissions that will require a transformation in the way buildings are heated, including major efforts in existing buildings. This transition is inextricably linked to existing energy equity issues that we believe significantly overlap across NYC (and elsewhere). These include unreliable heating in the winter, susceptibility to extreme heat (an increasing occurrence with climate change) and struggles to afford energy needs. Various known data sources for NYC are available, though they are disparate and have not been analyzed holistically. Further, we believe there are potential engineering and policy solutions to these challenges. In this project, the DSI scholar will access (and search for where not yet known to qSEL researchers) relevant data sets, analyze those data sets to identify communities exposed to all or a subset of these issues, and assist qSEL researchers in developing models to evaluate possible solutions. The project has the possibility of extending through Summer 2020, subject to fundraising efforts and the success of the Spring 2020 project.

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We have been studying bladder cancer in a mouse model of the disease and we are seeking to understand the molecular features of the mouse models as they relate to human bladder cancer.

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Single cell sequencing has generated unprecedented insight into the cellular complexity of normal and diseased organ. We are interested in using this technique to understand the mechanisms of eye development, disease and regeneration. We also would like to compare the transcriptomic signatures between mouse models and human tissues. This project involves analysis of large amount of data from single cell sequencing. It requires understanding of statistical analysis and proficient programming skills.

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Project: analyze behavior of Siamese fighting fish (Betta splendens) as part of a collaboration between the Bendesky and Cunningham labs of the Zuckerman Institute (NeuroTheory Center)

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The Urban Lead Atlas is a collaborative community-based research initiative to create the nations’ first crowd-sourced open online map identifying toxic lead hazards located within the homes, schools, landscape, and lead service lines for water in American cities. The project will begin by integrating data from a small set of cities – New York, Philadelphia, Washington D.C. and Newark - including housing enforcement and lead service line datasets, data on lead dust in schools, and the results of soil lead tests in parks and backyards, on the websites of Columbia University’s Center for Sustainable Urban Development. Ultimately, the goal of the Urban Lead Atlas is to create and populate a fully open online platform that is capable of integrating data from “citizen scientists” and residents regarding the sites of lead hazards in their city’s environment and buildings. This research is important, as experts estimate that over nine million US children have lead blood levels which may cause sub-clinical effects and permanent adverse health, cognitive, and behavior outcomes. The Lead Atlas is intended as the first model for a national effort, the American Lead Atlas project, which seeks to create a national online collaborative map of lead hazards within American cities.

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