At NYU, we believe that robotics has a central role to play in future urban environments and the improvement of human life, from mobility to healthcare, from infrastructure management to the service industry.

robot in motion

Robotics research and education at NYU focuses on developing and teaching the fundamental principles, theories, and algorithms for autonomous intelligent machines. Through our research and education, we aim to enhance mobility, service, infrastructure, and healthcare. Our mission is to carry out fundamental and multidisciplinary research to advance the science of robotics, to educate and mentor students in the theory and practice of robotics, and to make a positive impact on society.

Degree programs in robotics

professor 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.

Learn more about the Mechatronics and Robotics, M.S.


student hands working on robot

Undergraduate Minor in Robotics

The Robotics Minor consists of four undergraduate ROB courses. The minor teaches the fundamentals of robotics: kinematics, dynamics, manipulation, locomotion, planning, vision, and human-robot interaction. Students will have hands-on experience. Interested students should allow 4 semesters (two years) to complete the four courses for the minor in robotics.

More information about the robotics minor is available in the Bulletin.

Robotics Courses

Undergraduate Courses                     Graduate Courses

*Before taking undergraduate ROB courses, students should first take appropriate courses in math, physics, and computer science: Calculus (MA-UY 1124), Mechanics (PH-UY 1013), Programming (CS-UY 1114 or CS-UY 1133), Linear Algebra and Differential Equations (e.g., MA-UY 2034).

VIP Robotics Teams

Students* can earn credit by participating in Vertically Integrated Projects (VIPs) related to robotics.

*Projects marked with GY are open to graduate student participation 

Research Areas

  • Aerial robotics, autonomous drones
  • Autonomous ground vehicles
  • Control theory
  • Computer vision for robotics
  • Cyberphysical systems
  • Dynamical systems
  • Game theory and applications
  • Learning-based control
  • Legged locomotion
  • Machine learning
  • Mechatronics
  • Medical, surgical, and rehabilitation robotics
  • Navigation
  • Resiliency and security
  • Robotic manipulation
  • Stability and energetics

Labs and Groups

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.

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. 


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

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.

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. 

Laboratory for Agile and Resilient Complex Systems

Our goal is to develop new control and game-theoretic tools for designing agile and resilient control for smart energy systems, communication networks, secure cyber-physical systems, and human-in-the-loop systems.

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.


Farokh Atashzar 
Prof. Atashzar's research is in medical, surgical, and rehabilitation robotics. He also works on haptics, smart protheses, telerobotics, control theory, and AI. He organizes and chairs numerous workshops and symposia on these topics. Prof. Atashzar heads the MERIIT Lab.

Yi-Jen Chiang 
Prof. Chiang's research is in big data visualization and computation, including robot motion planning, I/O-efficient algorithms, information-theoretic data analysis and visualization, multiresolution techniques, graphics compression, computational geometry, and topology-driven visualization.

Anna Choromanska 
Prof. Choromanska's research is in machine learning (theory and applications), deep learning, optimization, and autonomous driving systems. Results of her work are in use by Facebook and Baidu. She has received an IBM faculty award and has been named an Alfred P. Sloan Fellow.

Chen Feng 
Prof. Feng's research is in computer vision and machine learning for robotics and automation. He has several patents on visual simultaneous localization and mapping. Prof. Feng's multidisciplinary research group, AI4CE, works on problems that originate from civil and mechanical engineering domains.

Zhong-Ping Jiang 
Prof. Jiang's current research is in learning-based control and distributed optimization/control for autonomous and nonlinear systems. He was named a Clarivate Analytics Highly Cited Researcher (2018) and is on numerous editorial boards. Prof. Jiang is the originator of robust adaptive dynamic programming which has applications to power systems, connected and autonomous vehicles, and human motor control. He is a Fellow of IEEE, IFAC, and CAA. He heads the CAN Lab.

Vikram Kapila 
Prof. Kapila's research is in mechatronics, robotics, smart sensors, and applications of control. He is a pioneer of mechatronics education and K-12 STEM education. Prof. Kapila has received numerous awards for teaching and innovation in education. He heads the Mechatronics Lab.

Farshad Khorrami 
Prof. Khorrami's research is in autonomous unmanned vehicles, smart structures, robotics, cyber-physical systems, high-speed positioning, large scale systems and decentralized control. He has multiple patents in micropositioning, vibration reduction, and actuator control. Prof. Khorrami heads the Control/Robotics Research Lab (CRRL).

Joo H. Kim 
Prof. Kim's research is in multibody system dynamics, optimization theory and algorithms, and control, with applications in robotics and biomechanical systems. His current interests include stability, energetics, and locomotion control of legged robots. Prof.Kim heads the Applied Dynamics and Optimization Lab.

Giuseppe Loianno 
Prof. Loianno's research is in aerial robotics, drones, and vision-based navigation. Much of his research has been highlighted in the media such as IEEE Spectrum (e.g., controlling a drone using eye-tracking glasses). Prof. Loianno heads the Agile Robotics and Perception Lab (ARPL).

Maurizio Porfiri 
In his research, Prof. Porfiri uses the theory and algorithms of dynamical systems and networks to model, analyze, and predict the behavior of environmental, social, and engineered systems. His research is frequently featured in the media. Prof. Porfiri is a Fellow of the IEEE and ASME. He heads the Dynamical Systems Lab.

Ludovic Righetti 
Prof. Righetti's research focuses on the control of movements for autonomous robots and he is more broadly interested in questions at the intersection of decision making, optimization, applied dynamical systems and machine learning, and their applications to physical systems. He heads the Machines in Motion Lab.

Nialah Wilson-Small 
Prof. Wilson-Small's research is in coordination algorithms for large collectives of simple robots, and human-drone interactions. Specifically, she is interested in how drones can use physical feedback to influence human motion, enhancing communication for novel applications.

Quanyan Zhu 
Prof. Zhu's research is in game theory for autonomous decision making, the design of resilient and secure cyber-physical systems, and resource allocation. His research has applications to smart and safe autonomous systems, power and transportation infrastructure security, health care economics, and public policy. Prof. Zhu heads the LARX Lab.

Selected Publications