RUCI Lab 3D Design Wins First Place

This map, created by Gavin Rozzi, showcases the diverse population density of New Jersey communities at the Census tract level through the use of 3D visualization techniques and selected annotations of municipalities. It took first place in NJDEP’s 34th Annual GIS Mapping Contest. The population density of each Census tract in New Jersey was computed […]

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Interactive Dashboard: Business Foot Traffic During Phase 1 NJ Lockdown

As a part of the RUCI Lab’s ongoing research into the social, economic and public health impacts of the COVID-19 pandemic in New Jersey through the use of data analytics, we have created an interactive dashboard that focuses on how foot traffic to local businesses has changed. Bloustein School MCRP/MPI graduate Haoyun Wang joined the […]

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Visualizing the Spread of COVID-19 in the United States

The New York Times created a public dataset tracking the spread of COVID-19 by county since the beginning of the year. This national, county-level dataset is a valuable resource for researchers and is a result of the collaborative effort journalists working across the country compiling information from public health authorities and other sources. As noted […]

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COVID-19 and Movement Patterns in New Jersey

Do you feel as if you have been at home for a long time during the COVID-19 pandemic? If yes, you are not alone. New Jersey instituted a stay-at-home policy on Saturday, March 21. As a part of a multiphase reopening process, NJ ended maximum restrictions and moved to Stage One Reopening on May 18, […]

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Medical and Health/Upstream Determinants of Health Informatics

The field of healthcare administration is concerned with better patient care and healthcare delivery. The RUCI Lab is interested in using emerging technologies and novel sources of data for analytics to improve upstream determinants of health such as transportation and air quality, as well as quality of care. Some of the work relates to using […]

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Social media analytics and event detection in transportation and cities

Social media data offers great potential to understand trends and patterns, real-time monitoring of disruptions and events, as well as sentiments, perceptions and beliefs. Yet, almost all social media data, whether it is microblogging data, or website data, are noisy and a mixture of text and images, and with provider restrictions and sampling restrictions to access.

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