Research Groups & Labs

Through the novel use of observational and analytical techniques, the Urban Observatory at the Center for Urban Science + Progress (CUSP-UO) studies the complex interactions between the physical, natural, and human components of the city as a coherent, definable system with the goal of enhancing public well-being, city operations, and future urban plans. 

Professor Maurizio Porfiri’s group conducts multidisciplinary research in the theory and application of dynamical systems, motivated by the objectives of advancing engineering science and improving society. Their theoretical expertise is in controls, networks, nonlinear dynamics, and time-series, while our application domain is in modeling and analysis of physical, social, and technical systems. 

The Immersive Computing Lab at NYU Tandon School of Engineering conducts cutting edge research that spans the fields of computer graphics, physics, and computational cognition, with the goal of creating unprecedented virtual and augmented reality systems to revolutionize urban life. Our research directions include novel multimodal/low-latency/immersive interaction devices, bio-physically inspired wearable displays, perception-aware VR/AR, and beyond.

The ML4G Lab is focused on development of novel machine learning methods for addressing critical urban problems and improving public health, safety, and security.

mLab is broadly interested in real-world security and privacy threats in healthcare and consumer technologies. Led by, Assistant Professor Danny Yuxing Huang, mLab builds systems to measure these threats at scale.

SONYC researchers have launched a citizen science initiative to train artificial intelligence (AI) technology to understand exactly which sounds are contributing to unhealthy levels of noise in New York City. A first-of-its-kind project addressing urban noise pollution, SONYC is based at NYU Tandon’s Center for Urban Science and Progress (CUSP).

Founded at NYU Tandon, the GovLab aims to strengthen the ability of institutions – including but not limited to governments – and people to work more openly, collaboratively, effectively and legitimately to make better decisions and solve public problems.

Urban Complexity Lab is unfolding complexity of urban systems for research, innovation and applications. We leverage big urban data and cutting-edge machine learning and network analysis techniques to make our cities more smart, efficient, sustainable, and resilient – better places to live in.

Our mission is to change the way urban engineering is done by bridging the gap between Civil Engineering and Computer Science. We focus on developing tools to better understand the urban built environment through pioneering new means to optimize and synthesize multi-modal data collection, storage, and processing.