Our mission is to design these electronic chips with built-in defense mechanisms, in order to expose any intentional malicious alteration of the chips and protect design IP from reverse engineering, exposedefective chips more easily and cost-effectively, and make them resilient to errors during mission mode. We develop Design-for-Excellence techniques comprising of hardware design blocks and accompanying software CAD tools.
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MoMA Lab focuses on security and privacy of modern high-performance and embedded microprocessors. Research topics include privacy-preserving architectures, encrypted computation, industrial control systems security, and hardware security.
Cyberphysical Systems Laboratory
The focus of CPSLab is to conduct interdisciplinary research across a wide range of topics and applications related to cyberphysical systems, such as: a) distributed algorithms for estimation, optimization, and control, b) big data: data mining/machine learning algorithms, c) wireless sensor networks, d) system theory: control & amp; optimization, e) signal processing: sparse sampling and online algorithms, as well as applications in power systems, transportation, cybersecurity, wireless networking, robotics, and biomedical modeling.
The Applied Interactive Multimedia (AIM) research group focuses on tangible interfaces and haptic technologies as a new media for interpersonal computer-mediated communication.
The Photonics Research Lab is working on the development of novel components for next generation optical and data communication networks. The Photonics lab is also interested in optics applications for cybersecurity, health care and environment monitoring. The overall goal of our lab is to explore the following areas: Silicon Photonics Integrated Circuits, Process technology for low-temperature germanium photodetectors and modulators, Energy-efficient Photonic sensors, Opto-MEMS, Cybersecurity, Microwave Photonics, Plasmonics
The Integrated BioElectronics Lab aims at advancing the engineering and applications of silicon integrated technology interfacing with biology in a variety of forms ranging from implantable biomedical devices to unobtrusive wearable sensors.
The L&G Lab focuses on problems at the interface of learning algorithms and game theory.
NYU Multimedia and Visual Computing Lab is an intellectual hub for faculty, researchers and students from both New York and Abu Dhabi campuses, who come together to study and address the key challenges in multimedia and visual data processing. Our lab is currently focused on the research and development of the state-of-the-art algorithms and methods for deep learning driven visual computing to address challenging issues such as 3D visual SLAM, 3D Point Cloud Processing, and 2D visual objects detection and recognition.
Blending theory with experiments, we focus on the behavior of networks with particular emphasis on synthetic biology applications. Research at the BioNet group is characterized by the duality of quantitative theory and experiments.