5 papers · 1 filter
TGDT: A Temporal Graph-based Digital Twin for Urban Traffic Corridors
Nooshin Yousefzadeh, Rahul Sengupta, Jeremy Dilmore +1
Urban congestion at signalized intersections leads to significant delays, economic losses, and increased emissions. Existing deep learning models often lack spatial generalizabilit…
Dynamic Graph Attention Networks for Travel Time Distribution Prediction in Urban Arterial Roads
Nooshin Yousefzadeh, Rahul Sengupta, Sanjay Ranka
Effective congestion management along signalized corridors is essential for improving productivity and reducing costs, with arterial travel time serving as a key performance metric…
Graph Attention Network for Lane-Wise and Topology-Invariant Intersection Traffic Simulation
Nooshin Yousefzadeh, Rahul Sengupta, Yashaswi Karnati +2
Traffic congestion has significant economic, environmental, and social ramifications. Intersection traffic flow dynamics are influenced by numerous factors. While microscopic traff…
MTDT: A Multi-Task Deep Learning Digital Twin
Nooshin Yousefzadeh, Rahul Sengupta, Yashaswi Karnati +2
Traffic congestion has significant impacts on both the economy and the environment. Measures of Effectiveness (MOEs) have long been the standard for evaluating traffic intersection…
LAVA: Granular Neuron-Level Explainable AI for Alzheimer's Disease Assessment from Fundus Images
Nooshin Yousefzadeh, Charlie Tran, Adolfo Ramirez-Zamora +3
Alzheimer's Disease (AD) is a progressive neurodegenerative disease and the leading cause of dementia. Early diagnosis is critical for patients to benefit from potential interventi…