Data Science / AI / Robotics
Three disciplines come together to create the technologies that will define the future.
Our AI experts and roboticists are working in concert with our data scientists, who are discovering new ways to analyze, visualize, and use their skills for a common goal: to harness the collective power of data, machine learning techniques, and autonomous systems to address the issues facing the world.
AI is everywhere. Can we make sure it's ethical?
AI powers so much of our world. It’s used by recruiters, police departments and businesses to help make their work more efficient. But with people’s lives on the line, can we trust that the algorithms behind AI are being created fairly? NYU Tandon researchers are helping to create an ecosystem where AI is critically analyzed to minimize the bias behind the code, and to ensure that these systems are used fairly and equitably whenever possible.
Better robotics through better data
At NYU Tandon, researchers are using 5G to connect autonomous teams of robots to complete tough and dangerous jobs, mimicking complex animal behaviors in remotely controlled robots, and creating cheaper, more accessible robots so that anyone can learn to program the next advancement in robotics. The future is here, and it’s being developed by our engineers.
Professor Zhong-Ping Jiang is widely recognized for his contributions to the stability and control of interconnected nonlinear systems, and is a key contributor to the nonlinear small-gain theory. Some of his most recent projects involve examining human motion in an attempt to expand our understanding of the brain and aid clinicians in devising new therapies for patients with neurodegenerative disorders; and providing mathematical control theory and algorithms for systems of nonlinear differential equations that are prone to uncertainties — work that could aid in fields as varied as marine biology and renewable energy networking.
Professor Juliana Freire is developing data management techniques and infrastructure to address problems introduced by emerging applications. Her recent work focuses on urban environments, using data from photography, the web and other sources to understand the ways we move and interact with the cities we live in. She has received several awards, including an NSF CAREER, an IBM Faculty award, and a Google Faculty Research award.
AI is becoming more and more prevalent in businesses, public services, and other parts of our lives. But when the algorithms behind AI are written with the same prejudices that marr our current society, it has the potential to deepen inequality, not overcome it. In this webinar, members of The Center for Responsible AI walk us through their perspectives on the use of AI and automation, and their recommendations to make sure responsible AI will be the only kind of AI used in the future in this seminar.
Research Labs and Groups
Agile Robotics and Perception Lab
Algorithms and Foundations Group
Applied Dynamics and Optimization Laboratory
Automation and Intelligence for Civil Engineering
Center for Responsible AI
Center for Urban Science and Progress (CUSP)
Control and Network (CAN) Lab
Control/Robotics Research Laboratory (CRRL)
Cybersecurity for Democracy
DICE (Data, Intelligence, and Computation in Engineering) Lab
Dynamical Systems Laboratory (DSL)
Hartman Research Lab
Machines in Motion
Mechatronics, Controls, and Robotics Lab
Medical Robotics and Interactive Intelligent Technologies (MERIIT)
NYU Tandon Future Labs
Sounds of New York City (SONYC)
The Governance Lab (The GovLab)
Visualization and Data Analytics ViDA Center