Data Dive Workshop: Exploring Urban Scaling in Crime Spatial Data

The Center for Urban Science + Progress (CUSP) at NYU Tandon welcomes you to participate in hybrid workshop titled "Exploring Urban Scaling in Crime Spatial Data" hosted by PhD students Inês Figueira, Tian Gan, and Rayan Succar of the Dynamical Systems Laboratory directed by Dr. Maurizio Porfiri, Director of CUSP and Institute Professor at NYU Tandon.This event will be held in a hybrid format—both in person at 370 Jay Street and livestreamed via Zoom. We’ll send the Zoom link to all attendees closer to the event.

Description

Understanding spatial patterns and scaling laws in urban systems is essential for analyzing complex social phenomena. In this short workshop, students will explore urban scaling theory and spatial autocorrelation through Moran’s I, gaining tools to study how city characteristics scale with population and how spatial patterns reveal underlying dynamics. The first part of the workshop introduces the theoretical foundations of urban scaling and spatial correlation. In the second part, students will apply these concepts to real-world crime data from Uruguay, learning to combine both approaches to uncover insights into urban crime distribution and intensity.

After the workshop, participants are encouraged to apply the skills they've learned to their own datasets and take part in a showcase event on Friday, July 25th. We’ll share more details and the event timing once participant numbers are confirmed for the workshop.

About the Speakers

Inês Figueira is a PhD student in NYU Tandon's Department of Mechanical and Aerospace Engineering, a participant in the Urban Science Doctoral Track, and a member of the Dynamical Systems Laboratory at CUSP. She obtained her Bachelor’s degree in Aerospace Engineering at the Instituto Superior Técnico of the University of Lisbon (Lisbon School of Engineering) in 2023. Her interests are focused on macro trends that have a significant impact on the space sector, especially in the global push for sustainability and smart cities. Inês aims to study complex urban systems and how they can benefit from space-integrated models and observational data to optimize mapping processes and data collection.

Tian Gan is a PhD student in NYU Tandon's Department of Mechanical and Aerospace Engineering, a participant in the Urban Science Doctoral Track, and a member of the Dynamical Systems Laboratory at CUSP. Tian's research focuses on developing network and graph-based models of complex urban systems. Tian is currently developing a multidimensional model that describes interactions between doctors and patients. This research will help increase the equitable distribution of medical care in cities and inform decision-making in public health.

Rayan Succar is a PhD student in NYU Tandon's Department of Mechanical and Aerospace Engineering, a participant in the Urban Science Doctoral Track, and a member of the Dynamical Systems Laboratory at CUSP. Rayan's work centers on stochastic complex dynamical systems, exploring both theoretical and applied perspectives. Specifically, Rayan investigates human behavior within these systems.

About the Center for Urban Science + Progress

The Center for Urban Science + Progress (CUSP) at NYU Tandon is an interdisciplinary center dedicated to applying science, technology, engineering, math, and social sciences to serve urban communities worldwide.

Founded as a partnership between NYU and the City of New York, CUSP leads research, educational, and entrepreneurial initiatives that advance the science of cities. By applying novel insights to urban issues, we develop data- and technology-driven approaches that drive positive impact. With an additional focus on training future leaders, CUSP offers interdisciplinary academic programs in applied urban science and informatics for graduate students and professionals.

CUSP also engages with stakeholders across city agencies, start-ups, industry players, community-based organizations, and nonprofits to address urgent socioeconomic, environmental, and infrastructural challenges. The center’s ultimate objective is to improve urban quality of life by using data to innovate and refine inclusive, equitable, and sustainable practices for cities everywhere.