Labs and Centers

The Algorithms and Foundations Group at NYU's Tandon School of Engineering is composed of researchers interested in applying mathematical and theoretical tools to a variety of disciplines in computer science. We study problems in machine learning, geometry, computational biology, computational mathematics, and beyond.

CATT promotes industry-university collaborative research and development in these areas: wireless and personal communications networks and devices, secure information technologies, and media and network applications/services.

The Center for Urban Science and Progress (CUSP) is an interdisciplinary research center dedicated to the application of science, technology, engineering, and mathematics in the service of urban communities across the globe. Using New York City as our laboratory and classroom, we strive to develop novel data- and technology-driven solutions for complex urban problems.

The overarching goal of our research is to develop the principles needed to incorporate unstructured, Internet and mobile data into a better understanding of population-level health. We primarily develop computational methods across data mining, natural language processing, and machine learning to generate features for spatio-temporal population-level public health models.

Cybersecurity for Democracy is a research-based, nonpartisan, and independent effort to expose online threats to our social fabric — and recommend how to counter them. We are part of the Center for Cybersecurity at the NYU Tandon School of Engineering.

The Data, Intelligence and Computation in Engineering (DICE) Lab is led by Assistant Professor Chinmay Hegde and focuses on theoretical and applied aspects deep learning and machine learning.

The Game Innovation Lab brings together faculty and students from the School of Engineering and the greater NYU community doing research focused on games as an innovation challenge. The Lab's emphasis is on the technical / engineering / science side of games and simulations. Sample projects include user interface innovation (sensor-based tracking, multi-touch), network and video quality research, and research on games for learning.

Using advances in computer vision and machine learning, Professor Guido Gerig’s team develops image analysis methodologies related to segmentation, registration, atlas building, shape analysis, and image statistics. Collaboratively with clinical research, this work is driven by medical problems covering research in autism, Down's syndrome, eye diseases, Huntington's disease, and musculoskeletal disorders.

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.

We develop computational models and signal processing tools to decode brain connectivity and function using genomics and imaging. We are particularly interested in constructing a bridge between genetics and behavior through interpretable models that operate on multi-modal neural data at molecular, circuit and whole-brain resolutions.

CCS is an interdisciplinary research institute dedicated to training the next generation of cybersecurity professionals and to shaping the public discourse and policy landscape on issues of technology and security. The Center is a collaboration among NYU Tandon School of Engineering and other NYU schools and departments.

The OSIRIS Lab is a student-run cybersecurity group that is part of the NYU's Center for Cyber Security.

The Secure Systems Laboratory (SSL), under the direction of Professor Justin Cappos, works to find practical and deployable solutions to real-world security threats.

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. 

ViDA consists of computer scientists who work closely with domain experts to apply the latest advances in computing to problems of critical societal importance, and simultaneously generate hypotheses and methods that new data demands.