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Labs

CILVR​

  • CILVR at NYU: The CILVR Lab (Computational Intelligence, Learning, Vision, and Robotics) regroups faculty members, research scientists, postdocs, and students working on AI, machine learning, and a wide variety of applications, notably computer perception, natural language understanding, robotics, and healthcare. Follow us @CILVRatNYU on Twitter!

  • ML² – Machine Learning for Language at NYU: The Machine Learning for Language (ML²) group is a team of researchers at New York University working on developing and studying state-of-the-art machine learning methods for natural language processing (NLP). ML² is affiliated with the larger CILVR lab.

  • Math and Data: The Math and Data group is part of New York University’s Center for Data Science, and the Courant Institute of Mathematical Sciences. Its mission is to advance the Mathematical and Statistical foundations of Data Sciences, specializing in Signal processing and Inverse Problems, Machine Learning and Deep Learning, and High-dimensional statistics and Probability.

  • Human & Machine Learning Lab: Today’s AI provides nothing like the general purpose, flexible intelligence that we have as humans. We are studying the ingredients of intelligence that enable fast and flexible learning. Join us.

NYU Wireless​

  • NYU WIRELESS | Terahertz, 6G & Beyond: NYU WIRELESS is a vibrant academic research center that is pushing the boundaries of wireless communications, sensing, networking, and devices.

  • Medical Robotics and Interactive Intelligent Technologies (MERIIT@NYU) Laboratory –: The mission of the MERIIT Lab is to develop Intelligent human-centered Robotic Systems, neural interfaces, Advanced Control Modules, Bio-Signal Processing Algorithms, and Smart Wearables to augment human capabilities beyond natural competence. A particular focus of the lab is on interactive Neuro-Rehabilitation Robotic and Surgical Robotic systems. The lab hosts state-of-the-art human-machine interface technologies to exploit bidirectional interactions that allow humans to overcome natural, physiological, and pathological barriers.

  • NYU Video Lab: The NYU Video Lab is led by Prof. Yao Wang and consists of about 10 Ph.D. and M.Sc. students. Research activities in our lab encompass many areas related to video processing and communication, medical image analysis and computer vision.

  • NYU Nanolab – Laboratory for Nanoelectronics Research: Our research team studies the physics of electronic materials and their application in building devices and circuits. We are an experimental group with experience in the synthesis of layered materials, nanofabrication of electronic devices, and electrical measurements at both room and cryogenic temperatures.

  • CommIT Group at NYU: Welcome to the Communication and Information Theory (CommIT) Group at New York University, led by Professor Elza Erkip. We are interested in theoretical foundations of networks, including wireless and social networks.

NYU Systems​

  • Systems@NYU: Our group works on large-scale distributed computing, security, systems aspects of Big Data, low-cost computing for the developing world, and millimeter wave wireless.

  • NYU Open Networks and Big Data - Home: We are a team of researchers in the Courant Institute of Mathematical Sciences at New York University, focusing on research at the intersection of machine learning and networked systems. We are part of the NYU Systems group in the Computer Science Department.

NYU Center of Data Science​

  • NYU Minds, Brains, and Machines Initiative: Understanding intelligence is one of the greatest scientific quests ever undertaken—a challenge that demands an interdisciplinary approach spanning psychology, neural science, philosophy, linguistics, data science, and artificial intelligence (AI). A focus on computation is at the center of this quest—viewing intelligence, in all of its forms, as a kind of sophisticated and adaptive computational process. But the kind of computation necessary for intelligence remains an open question; despite striking recent progress in AI, today's technologies provide nothing like the general-purpose, flexible intelligence that we have as humans.

  • STAT Research Group – NYU Center for Data Science: The STAT group (Statistics: Tools, Algorithms, and Theory) seeks to advance the state-of-the-art in statistics, by developing new methodological, computational, and mathematical approaches to statistical problems and to their applications in data science and machine learning. The STAT group assembles faculty, fellows and students across CDS and the Courant Institute.

Tandon:​

  • AI4CE Lab: The AI4CE (pronounced as “A-I-force”) lab at New York University conducts multidisciplinary use-inspired research. We aim to advance fundamental automation and intelligence technologies such as robot vision and machine learning, while addressing challenges of their applications in civil and mechanical engineering domains.

  • VIDA: The Visualization and Data Analytics Research Center at NYU 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 sources and data types demand.

  • Algorithms and Foundations: We are the Algorithms and Foundations Group in the Computer Science and Engineering Department at NYU's Tandon School of Engineering. Our group is composed of researchers interested in applying mathematical and theoretical tools to a variety of disciplines in computer science, from machine learning, to systems, to geometry, to computational biology, and beyond. You can visit our individual webpages to learn more.

  • CanLab: ​The Control and Network (CAN) Lab is led by Professor Zhong-Ping Jiang and consists of about 10 people. Research activities in the CAN Lab mainly focuses on the development of fundamental principles and tools for the stability analysis and control of nonlinear dynamical networks, with applications to information, mechanical and biological systems.

  • C2SMART: C2SMART, a USDOT Tier 1 University Transportation Center, uses cities as living laboratories to study challenging transportation problems and find solutions from the unprecedented recent advances in communication and smart technologies. Our core mission includes addressing:

  • CATT – Center for Advanced Technology in Communications: The Center for Advanced Technology in Telecommunications and Distributed Information Systems (CATT) promotes industry-university collaborative research and development. Our mission, guided by the mission of our funding agency, is to create economic impact through research, technology transfer, and faculty entrepreneurship. The CATT is sponsored by the New York State’s Empire State Development’s Division of Science, Technology and Innovation (NYSTAR).

  • NYU mLab: We are broadly interested in real-world security and privacy threats in healthcare and consumer technologies (see this video). We build systems to measure these threats at scale. Our techniques are heavily based on empirical measurements—hence our name, NYU mLab (also short for momoLab).

  • Secure Systems Lab: The Secure Systems Laboratory (SSL) at New York University's Tandon School of Engineering identifies and designs solutions for security threats to software systems

  • High Speed Research Network: NYU IT - High Speed Research Network (HSRN) is a division of Research Technology focused on powering real time “closed loop” research through the seamless integration of advanced network infrastructure and applications. Through offerings of high speed networking, edge compute solutions, and powerful network applications developed by our team such as Corelink, we enable NYU researchers to harness experiments and applications that utilize data efficiently in real time in domains such as applied physics, audio engineering, AR/VR, computational chemistry, IoT, AI, and much more.

  • SONYC: SONYC research initiative combines sensors, big data, and machine learning to understand, model and influence NYC’s acoustic environment

  • Control/Robotics Research Laboratory (CRRL): The Control/Robotics Research Laboratory is located at NYU Tandon School of Engineering (Polytechnic Institute), NYU, Brooklyn, New York. The laboratory was set up in 1989 by Prof. Farshad Khorrami. The CRRL has been supported by the University and through grants and equipment donation from NSF, ARO, IBM, AT&T Foundation, and many other industrial organizations.

  • Agile Robotics and Perception Lab: The agile robotics and perception lab performs fundamental and applied research in the area of robotics autonomy. The main mission of the lab is to create agile autonomous machines that can navigate all by themselves using only on-board sensors in unstructured, and dynamically changing environments and without relying on external infrastructure, such as GPS or motion capture systems. The machines need to be active, they should collaborate with humans and between each other and they need to navigate in the unknown environment extracting the best knowledge from it.

  • Building22: Our goals are to advance integrative research in emerging media, virtual production, and other topics relevant to experiential computing; provide our industry partners with first-hand contact with both NYU faculty and students and cultural and media organizations in New York City; and bring research-grade emerging technology within reach of media, entertainment, and cultural sectors in New York City, allowing companies, museums and other arts organizations, and independent creatives to have an equitable platform in which to engage in new tools and techniques.

  • NYU CUSP: A unique academic research center at the NYU Tandon School of Engineering dedicated to the interdisciplinary application of science, technology, engineering, and mathematics in the service of urban communities across the globe.

  • SCG | Systems and Control Group: The mission of the systems and control group is to model and design intelligent and autonomous systems. Initially developed in the context of electric circuits, recent applications have focused on complex, dynamic and networked systems, such as unmanned vehicles and power system networks. The field of system and control provides essential enabling and supporting technologies for different applications in electrical engineering ranging from defense and manufacturing to telecommunications and bioengineering. NYU School of Engineering has a long history of research in the area. Members of the group seek control tools and solutions for increasingly complex systems such as cyber-physical systems, neural systems, swarms of robots, or economic markets.

  • Mechatronics, Controls, and Robotics Lab: The exciting field of Mechatronics - increasingly recognized as a contemporary, integrative design methodology - is serving as a vehicle to engage and stimulate the interest of NYU Tandon students in hands-on, interdisciplinary, collaborative learning. Mechatronics is a synergistic integration of mechanical engineering, control theory, computer science, and electronics to manage complexity, uncertainty, and communication in engineered systems. The typical knowledgebase for the optimal design and operation of Mechatronics and smart systems comprises of system modeling and analysis, decision and control theory, sensors and signal conditioning, actuators and power electronics, hardware interfacing, rapid control prototyping, and embedded computing.

  • LARX | Laboratory for Agile and Resilient Complex Systems: Research activities at LARX mainly focuses on the development of fundamental principles and tools for secure, resilient and sustainable dynamical systems and networks, with applications to communication networks, cyber-physical systems and modern critical infrastructures.

  • Immersive Computing Lab: 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.

  • Machines in Motion: We are the Machines in Motion laboratory and we conduct fundamental and applied research in robotics. We strive to discover the algorithmic foundations of robotic movements as we believe that understanding how machines should move and interact with unknown environments is central for creating truly autonomous robots. In particular, we aim to conceive general methods applicable to any robots with arms and legs endowing them with the ability to robustly and safely perform any locomotion and manipulation tasks in unknown environments and to constantly improve their performances as they experience the world.

  • NYU Tandon School of Engineering Game Innovation Lab: Welcome to the Game Innovation Lab at the NYU School of Engineering, where we’ve been encouraging creativity and teamwork, and building innovative and playful experiences for our students, faculty, and visitors since 2011.

  • Future Reality Lab: Emulating the potential of future capabilities of small high quality VR/AR that will enable computer-supported face-to-face communication

NYU ECE:​

  • EnSuRe Research Group – Energy-Aware, Secure and Reliable Computing: Our research is at the intersections of computer hardware design, cyber-security, and machine learning with a focus on building energy-efficient (En), secure (Su), and reliable (Re) computing systems. We are always looking for talented students to join our group. If you are interested please e-mail Prof. Siddharth Garg.

  • BAAHL | Brooklyn Application, Architecture, and Hardware Lab: 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.

NYU Center of Cybersecurity:​

  • NYU Center for Cyber Security: NYU’s Center for Cybersecurity (CCS) is an interdisciplinary academic center in which leading edge research, teaching, and scholarship are directed into meaningful real-world technology and policies.

  • MESS Lab: Our research focuses on Machine Learning, Embedded Systems, and Software/Systems Security. The MESS Lab is part of the NYU Center for Cybersecurity.

  • 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.

  • NYU OSIRIS Lab: We are the Offensive Security, Incident Response, and Internet Security (OSIRIS) Lab: a student-run cybersecurity research lab and club at New York University.

NYU Stern:​

  • Data Analytics at the Fubon Center: The Fubon Data Analytics and AI Initiative brings together scholars, managers, and students to conduct and disseminate world-class research on data analytics, artificial intelligence, and data science for business. The Center brings people together, funds research, and engages in community outreach to support data analytics research that is both rigorous and accessible.

NYU Courant:​

  • The Proteus Project at NYU: Members of the Proteus Project have been doing Natural Language Processing (NLP) research at New York University since the 1960's. Our long-term goal is to build systems that automatically find the information you're looking for, pick out the most useful bits, and present it in your preferred language, at the right level of detail. One of our main challenges is to endow computers with linguistic knowledge. The kinds of knowledge that we have attempted to encode include vocabularies, morphology, syntax, semantics, genre variation, and translational equivalence.

  • Geometric Computing Lab @ NYU: We develop algorithms and mathematical foundations for computational problems involving complex geometry. Our emphasis is on development of robust and scalable algorithms applicable to a broad range of problems. We work on techniques for key geometry processing problems, such as parametrization and meshing, and on a diverse set of applications in computer graphics, scientific computing (complex flows in particular), and computational fabrication. We strive to make the software, datasets, and educational materials resulting from our research and teaching activities freely available.

  • Fourier Methods Project: The Courant Mathematics and Computing Laboratory (CMCL) is a research center at the Courant Institute of New York University. Our program is devoted to the formulation, analysis and numerical resolution of a broad class of scientific problems, drawn from aerodynamics, multi-phase flow, combustion, electromagnetics, optics and materials science. One component of the CMCL involves the design of new schemes for partial differential equations, particularly those which support adaptive mesh refinement, fast algorithms, and parallel computation. A second component of our effort concerns the modeling and numerical investigation of a variety of questions in materials science, complex fluid dynamics, interface motion, and electromagnetics. The third component of the CMCL involves the mathematical analysis of stochastic problems that arise in physics and Monte Carlo methods for their solution.

  • Fast Algorithms: Large-scale linear systems arise in a myriad of areas in physics, mathematics, and statistics. Often when directly discretizing PDEs, the resulting linear systems are sparse and efficient methods for applying the discretized operators are straightforward, and relatively efficient methods for computing their inverse has been developed. However, linear systems arising from the discretization of integral formulations of the very same PDEs are dense, and somewhat more sophisticated algorithms must be developed in order to apply and invert there operators with near optimal computational complexity. Often these algorithms are based on the underlying physics of the problem, and are therefore commonly referred to as analysis-based fast algorithms.

  • ai @ NYU: We are in the middle of an Artificial Intelligence revolution. Its impact is already great in many spheres of human undertaking and across disciplines, from social sciences to new material and drug discovery, to better decision-making in health, business, and government. NYU researchers play a major role in the AI revolution; we are the home of many stellar faculty in both AI research and AI applications. AI@NYU highlights the many activities in AI at NYU. Please browse the various sections of the site and reach out to us with any questions!

  • Dynamical Systems Group: Dynamical systems theory and applications, geometric and ergodic theory of chaotic systems, connections to probability and statistical physics, computational modeling and theoretical neuroscience

NYU Langone Health:​

  • Center for Healthcare Innovation & Delivery Science | NYU Langone Health: The Center for Healthcare Innovation and Delivery Science (CHIDS) is a group of clinicians, researchers, educators, and administrators who work together to redesign healthcare. Our mission is to improve patient health and wellbeing by fostering the development of effective, efficient, and patient-centered healthcare systems at NYU Langone Health and nationally. To do this, we conduct and support novel healthcare delivery redesign interventions, provide evaluations of existing intervations across our system, make use of new digital design and clinical informatics methods, create and deploy predictive analytic models, explore the effects of national and local policies on outcomes, and provide training in healthcare delivery science.

  • Center for Advanced Imaging Innovation and Research • Center for Advanced Imaging Innovation and Research: CAI2R creates technologies for better acquisition, reconstruction, and analysis of medical images. Our innovations advance research in biomedicine and our best technologies become leading-edge tools in clinical radiology.

  • Advanced Ophthalmic Imaging Lab: The Advanced Ophthalmic Imaging Lab at NYU Langone is a team of ophthalmologists, engineers, software specialists, statisticians, and trainees that focus primarily on glaucoma research.

Across Schools:​

  • NYU Ability Project: AN INTERDISCIPLINARY RESEARCH SPACE DEDICATED TO THE INTERSECTION BETWEEN DISABILITY AND TECHNOLOGY. We foster collaboration between assistive technology users, engineers, designers, educators, artists, occupational and physical therapists, speech language pathologists, and disability consultants. The Ability Project is open to all NYU students and faculty looking to create inclusive systems, design human­-centered projects, and further understanding and research in the area of ability.

  • Urban Intelligence Lab: The Urban Intelligence Lab, and its Civic Analytics program, works directly with city agencies and non-profit organizations to conduct rigorous, problem-oriented research that serves the dual purpose to advance our scientific understanding of cities and have a direct impact on public sector decision-making. Our goals are to bring evidence to policy-making, to democratize knowledge through information transparency, and to analyze and address the root causes and disparate impact of discrimination and bias embedded in urban analytics.

Other:​

  • OLAB: We’re interested in human and artificial intelligence. We use artificial intelligence (AI) to better understand and care for the human brain, and in study the human brain to build better AI.

  • Applied Dynamics and Optimization Laboratory: Our lab’s broad research areas include dynamics, control, and optimization of mechanical systems. Main domains for implementations and applications include robotic and biomechanical systems and their intersections such as lower-body wearable robots.

  • FOX LAB: We aim to empirically answer relevant questions about personality and cognition. Conducting studies at high statistical power and with epistemic integrity is an overriding focus. Institutionally, the lab is situated at the intersection between Data Science, Psychology and Neuroscience, reflecting the inter-disciplinary nature of our research interests.Importantly, we also aim to communicate our findings in a clear and accessible fashion – be it in presentations, publications as well as public outreach.

  • NYU Urban Modeling: Our mission is to bridge the gap between civil engineering and computer science to advance and expand the field of urban engineering. 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. These tools work together to auto-generate high-resolution, functional models appropriate for engineering analysis and datasets of unprecedented density, comprehensiveness, and richness, which our group generates, aids this process.

  • Computational Neuroimaging Laboratory » Home: The focus of the research in our lab is to develop a theory for the computations performed by neural circuits in the brain to quantitatively investigate the relationship between brain and behavior. Click on the Research tab for further details.

  • computation & cognition lab @ nyu: Our lab is interested in understanding the everyday forms of intelligence that make humans so smart. Despite recent advances, human intelligence still vastly out performs the abilities of our most intelligent machines such as robots, driverless cars, and virtual assistants. We want to understand why that gap exists and how to narrow it. However, what does it mean to "understand" something like intelligence?

  • NYU Alignment Research Group: The NYU Alignment Research Group (ARG) is a set of researchers doing empirical work with language models that aims to address longer-term concerns about the impacts of deploying highly-capable AI systems. See our introductory post for more on what this is about and why we started this initiative.

  • Music and Audio Research Laboratory | NYU Steinhardt: Music and Audio Research Laboratory is an interdisciplinary center at the intersection of science, technology, music and sound, with research connecting a wide range of fields from computing and artificial intelligence, immersive experiences and algorithmic composition, to the latest advances in neuroimaging of the human brain. Our work focuses on (a) understanding and modeling the human cognitive and neural mechanism supporting music and sound processing, (b) innovating the analysis, organization and retrieval of acoustic data, and (c) advancing applications of high societal value in health, accessibility, creativity, and education.

  • NYU Music Experience Design Lab: The NYU Music Experience Design Lab (MusEDLab) researches and designs new technologies and experiences for music making, creative learning and engagement together with students, educators, non-profit, and industry partners. We focus on lowering barriers to and promoting creative expressions of all people across the lifespan. With locations in Brooklyn and Shanghai, the MusEDLab actively seeks collaborators and partners in the US, Europe, and Asia.

  • NYU CTED: The Center for Technology and Economic Development (CTED) focuses on the development of innovative and cutting-edge technologies to significantly impact economic development with a specific focus on problems faced in underdeveloped areas around the world. Spanning Africa, Asia, and the Gulf, CTED’s research covers economic theory, global labor markets, migration, and the impact of technology on development.

  • Machine Learning for Good Laboratory: Our lab is focused on development of novel machine learning methods for addressing critical urban problems. By creating, deploying, and evaluating new methods in collaboration with public sector partners, we hope both to advance the state of the art in machine learning and to improve the quality of public health, safety, and security. We are particularly interested in solving challenging urban problems where off-the-shelf machine learning methods are insufficient and new innovations are required.

  • Climate & Ocean Physics @ NYU: Our group aims to advance the fundamental understanding of ocean dynamics and its role in the climate system in order to improve climate change projections.