UROP Research Mentor Project Submission Portal: Submission #1030

Overall Research Project Description This project aims to harness the power of large-scale, diverse, and real-time urban data to address critical challenges in city planning, sustainability, mobility, and public services. As cities become increasingly digitized, massive volumes of data, ranging from traffic flows, environmental sensors, social media, utility usage, and public transit records, offer unprecedented opportunities to understand and improve urban systems. However, effectively analyzing and visualizing these heterogeneous data sources to support timely and effective decision-making remains a significant challenge.

This research project will develop a comprehensive urban big data analytics and visualization framework that integrates spatiotemporal data mining, machine learning, and interactive visualization techniques to support smart city applications. Specifically, the project will:

Design scalable data pipelines to collect, clean, and integrate multimodal urban data streams;

Develop advanced analytics models to detect patterns, predict urban dynamics, and identify anomalies in domains such as mobility, energy consumption, housing, and public health;

Create intuitive, user-centered visualization tools that enable policymakers, city planners, and community stakeholders to explore insights, simulate scenarios, and support evidence-based decision-making.