10 papers
Do LLMs Know Your Neighborhood? Auditing LLM Priors for Neighborhood-Level Mobility Prediction and Structural Alignment
Saad Mohammad Abrar, Eesha Kurella, Arnav Dadarya +3
Human mobility is central to urban planning, transportation, public health, and emergency response, yet fine-grained trajectory data are often proprietary, restricted, and privacy-…
From "I have nothing to hide" to "It looks like stalking": Measuring Americans' Level of Comfort with Individual Mobility Features Extracted from Location Data
Naman Awasthi, Saad Mohammad Abrar, Daniel Smolyak +1
Location data collection has become widespread with smart phones becoming ubiquitous. Smart phone apps often collect precise location data from users by offering \textit{free} serv…
Systematic analysis of the effectiveness of adding human mobility data to covid-19 case prediction linear models
Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak +1
Human mobility data has been extensively used in covid-19 case prediction models. Nevertheless, related work has questioned whether mobility data really helps that much. We present…
Network-Based Transfer Learning Helps Improve Short-Term Crime Prediction Accuracy
Jiahui Wu, Vanessa Frias-Martinez
Deep learning architectures enhanced with human mobility data have been shown to improve the accuracy of short-term crime prediction models trained with historical crime data. Howe…
Improving the Fairness of Deep-Learning, Short-term Crime Prediction with Under-reporting-aware Models
Jiahui Wu, Vanessa Frias-Martinez
Deep learning crime predictive tools use past crime data and additional behavioral datasets to forecast future crimes. Nevertheless, these tools have been shown to suffer from unfa…
DemOpts: Fairness corrections in COVID-19 case prediction models
Naman Awasthi, Saad Abrar, Daniel Smolyak +1
COVID-19 forecasting models have been used to inform decision making around resource allocation and intervention decisions e.g., hospital beds or stay-at-home orders. State of the…
COVID-19's Unequal Toll: An assessment of small business impact disparities with respect to ethnorace in metropolitan areas in the US using mobility data
Saad Mohammad Abrar, Kazi Tasnim Zinat, Naman Awasthi +1
Early in the pandemic, counties and states implemented a variety of non-pharmacological interventions (NPIs) focused on mobility, such as national lockdowns or work-from-home strat…
Assessing the Impact of Case Correction Methods on the Fairness of COVID-19 Predictive Models
Daniel Smolyak, Saad Abrar, Naman Awasthi +1
One of the central difficulties of addressing the COVID-19 pandemic has been accurately measuring and predicting the spread of infections. In particular, official COVID-19 case cou…
Auditing the Fairness of the US COVID-19 Forecast Hub's Case Prediction Models
Saad Mohammad Abrar, Naman Awasthi, Daniel Smolyak +1
The US COVID-19 Forecast Hub, a repository of COVID-19 forecasts from over 50 independent research groups, is used by the Centers for Disease Control and Prevention (CDC) for their…
Comparing E-bike and Conventional Bicycle Use Patterns in a Public Bike Share System: A Case Study of Richmond, VA
Yifan Yang, Elliott Sloate, Nashid Khadem +2
The results show that pedelecs are generally associated with longer trip distances, shorter trip times, higher speeds, and lower rates of uphill elevation change. The origin-destin…