Data Science / AI / Robotics

The collaboration between these fields is generating world-changing technologies.

We’re making enormous inroads in the growing fields of AI and robotics, creating drones controlled with a simple gaze, making it easier for surgeons to perform delicate operations, developing algorithms that make financial investing more secure, and other such improvements.


robotic head and numbers


Our AI experts and roboticists are working in concert with our data scientists, who are discovering new ways to analyze, visualize, and use the 2.5 quintillion bytes of data the world generates each and every day in the form of GPS signals, shopping transactions, taxi rides, social media posts, online videos, and digital photos, among other sources. It’s a collaborative ecosystem with a single goal: to harness the collective power of data, machine learning techniques, and autonomous systems to address the issues facing the world.    More on Robotics

Academic Programs

girl working at laptop

Computer Science, B.S.

Computer science focuses on designing, building, and using the computers and systems that we interact with every day — from iPhones to the complex databases in banks and hospitals.
On Campus

electrical plans abstract

Electrical and Computer Engineering, B.S.

Electrical Engineering and Computer Engineering are both extremely pertinent in today's high technology and global world, and this program gives students opportunities to garner knowledge from both disciplines.
On Campus

STS

Science and Technology Studies, B.S.

Science and Technology Studies (STS) explores the human dimensions of science, technology and engineering (New applicants are no longer being accepted to this program).
On Campus

Mechanical Engineering Gears

Mechanical Engineering, B.S.

Mechanical engineering builds the physical systems and devices that define modern society — everything from air conditioning to automobiles, robots to power plants, artificial limbs to escalators.
On Campus

Bioinformatics

Bioinformatics, M.S.

A 30 credit, 10 course fully online master’s degree. Explore how our curriculum will provide you the background needed in Translational or Laboratory Sciences.
Online

Abstract image of human muscular system

Biomedical Engineering, M.S.

Biomedical engineering, a multi-disciplinary field, is behind some of the most important medical breakthroughs today, and has significantly contributed to improved health care and quality of life.
On Campus

Motherboard Chip

Computer Engineering, M.S.

Computer engineering makes it possible for us to telecommute from home and check our e-mail on the go, and even reconstruct genomes and conceive software to make businesses more efficient.
On Campus

Financial Engineering

Financial Engineering, M.S.

With a dynamically changing global world, our program trains our financial engineers to adapt theoretical and financial constructs into profitable and innovative opportunities.
On Campus

Professor  Righetti working in robotics lab

Mechatronics and Robotics, M.S.

Students in this program learn fundamental theory, modeling methods, hardware components, interfacing requirements, simulation and programming tools, and practical applications of mechatronics and robotics.
On Campus

code on screen

Computer Science, Ph.D.

Ph.D. students in our Computer Science program can conduct groundbreaking research with the faculty of our interdisciplinary Center for Cyber Security.
On Campus

circuit board

Electrical Engineering, Ph.D.

The Ph.D. in Electrical Engineering program is filled with students and faculty who prize the School of Engineering's emphasis on invention, innovation, and entrepreneurship through top-flight laboratories and a fierce dedication to advanced research.
On Campus

close up of hands soldering part of computer chip

Mechanical Engineering, Ph.D.

Our Ph.D. in Mechanical Engineering program offers a balanced curriculum that emphasizes the principles behind designs and approaches, and we make computational and research experience an integral component of your studies.
On Campus

Research Labs and Groups

View Configuration

Agile Robotics and Perception Lab

ARPL performs fundamental and applied research in robot autonomy. The lab develops agile autonomous drones that can navigate on their own using only onboard sensors without relying on maps, GPS or motion capture systems.

VISIT WEBSITE

AI4CE Lab

The AI4CE Lab works to advance fundamental automation and intelligence technologies, to enable their use in civil and mechanical engineering applications.

VISIT WEBSITE

Algorithms and Foundations Group

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.

VISIT WEBSITE

Applied Dynamics and Optimization Laboratory

We aim to establish mathematical models, quantitative criteria, and algorithmic/computational foundations toward their implementations in robotics (for design and control), biomechanical systems (for prediction and analysis), and their intersections such as lower-body wearable robots. 

VISIT WEBSITE

Brooklyn Application, Architecture, and Hardware Lab (BAAHL)

Led by Prof. Brandon Reagen, our research group specializes in computer hardware design, with a primary goal of making privacy-preserving computation practical. 

We also focus on optimizing machine learning systems for private computation. With a strong emphasis on energy-efficiency and security, our work aims to accelerate secure computation and enable privacy-preserving machine learning.

VISIT WEBSITE

Building Informatics and Visualization Lab (BiLab)

The Building Informatics and Visualization Lab (biLAB) is part of the Department of Civil and Urban Engineering at the NYU School of Engineering. It focuses on understanding the operational challenges associated with construction and operation of facilities and infrastructure systems in urban settings.

VISIT WEBSITE

Center for Responsible AI

The Center for Responsible AI at NYU Tandon is creating new ways of keeping AI unbiased, and training the next generation of experts to design technology that’s powerful and effective, but also equitable and fair.

VISIT WEBSITE

Center for Urban Science + Progress (CUSP)

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.

VISIT WEBSITE

Chunara Lab

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.

VISIT WEBSITE

Computational Medicine Laboratory

Professor Rose Faghih group develops biomedical signal processing and control algorithms for human-technology interactions and monitoring. These state-of-the-art tools are employed for prognosis, diagnosis, and treatment of pathological conditions related to neuro-endocrine and neuro-psychiatric disorders.

VISIT WEBSITE

Control and Network (CAN) Lab

The CAN Lab, led by Professor Zhong-Ping Jiang, develops fundamental principles and tools for the stability analysis and control of nonlinear dynamical networks, with applications to information, mechanical, and biological systems.

VISIT WEBSITE


Cybersecurity for Democracy

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.

VISIT WEBSITE


Dynamical Systems Laboratory (DSL)

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. 

VISIT WEBSITE

Hartman Research Lab

The Hartman Research Laboratory investigates the kinetics of chemical reactions and the design of the reactors in which they take place. Catalysis and reaction engineering is at the heart of virtually every process or system in which a chemical transformation occurs.

VISIT WEBSITE

Laboratory of Computational Multiomics

Professor Ruggles’ laboratory focuses on understanding human health and biology using data science, data visualization, and predictive modeling. A primary goal of this research is to analyze and integrate diverse data modalities, including bulk and single-cell sequencing, phospho- and global- proteomics, metagenomics, flow cytometry, imaging, and clinical data. These multi-omic methods are used to better understand cancer, heart diseases, and other disorders.

VISIT WEBSITE


Machines in Motion

We try to understand the fundamental principles for robot locomotion and manipulation that will endow robots with the robustness and adaptability necessary to efficiently and autonomously act in an unknown and changing environment.

VISIT WEBSITE



NanoBioX

The NanoBioX initiative at NYU stimulates fundamental research and technological innovation at the intersection of nanotechnology, biomedical research, and data science.

VISIT WEBSITE

Neural Circuits and Algorithm Group

The aim of Dr. Chklovskii’s research is to understand how the brain analyzes large and complex datasets streamed by sensory organs. Informed by anatomical and physiological neuroscience data, his group develops algorithms that model brain computation and solve machine learning tasks. The overarching goal it to build artificial neural systems and treating mental illness.

VISIT WEBSITE

NYU Tandon Future Labs

The NYU Tandon Future Labs are the first public-private partnership with New York City tasked with creating a sustainable incubation program focused on increasing the success rate of new ventures and generating positive economic impact.

VISIT WEBSITE

Social Behavior Neuroscience Lab

Social behaviors such as fighting, defense, and parenting, are innate and ubiquitous across the animal kingdoms. The research in Dr. Lin’s laboratory centers on understanding the neural circuits underlying these behaviors. Various genetic engineering, tracing, functional manipulation, in vivo electrophysiological recording and computational tools are combined to dissect the neural circuits in a great detail.

VISIT WEBSITE

Sounds of New York City (SONYC)

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).

VISIT WEBSITE

Urban Complexity Lab (UCOMP)

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.

VISIT WEBSITE

Urban Modeling Group

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. 

VISIT WEBSITE

Visualization and Data Analytics Center

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.

VISIT WEBSITE