Principles of mathematical statistics play an important role in signal, image, and video processing. Current projects examine statistical signal processing problems that arise in distributed sensor networks, wireless communications, as well as those related to machine learning and their applications. Other projects use statistical methods to solve inverse problems, primarily in imaging for emission and transmission tomography and magnetic resonance imaging. Notre Dame research in this area played a pioneering role in the development of principles and applications of Set-Membership Adaptive Filters.

Notre Dame research in wireless networking is centered in Notre Dame's Wireless Institute. The institute's work focuses on wireless communications system engineering including fundamental limits and tradeoffs from information theory, practical algorithms from coding and signal processing, and prototyping as well as experimental validation with software-defined radios. Technologies build upon models for novel network architectures and transceiver hardware, and are realized within the physical, medium-access control, and link layers of traditional protocol stacks. Much of this work is centered at Notre Dame's research center for wireless networking ( Wireless Institute) and the ND led NSF center on Spectrum Management (SpectrumX).

Advances in computing and networking technologies have made it easy to network systems together. Examples of such systems are found in communication infrastructure, eletrical power systems, and manufacturing. Research in Networked Control System engineering focuses on regulating a system's dynamics in a way that balances the limited capacity of the communication infrastructure against the stability/performance of the physical system.

Machine learning (ML) uses finite data sets to train models that predict how complex systems behave. ML has become a hot topic as a result of advances in deep neural networks and the computational hardware realizing these networks. Notre Dame's research explores Machine Learning in sensing and control. Faculty are involved with the development of hardware architectures for high-speed/low-power ML applications. Recent work is investigating issues regarding federated learning and robustness to out-of-distribution data.

Notre Dame's research in this areas addresses reliable communication over unreliable and constrained communication links. Current work focuses on the changing role that channel codes play in the context of wireless networks. Elements of this work include design of capacity-approach channel codes (e.g. LDPC and fountain codes), techniques for cooperative diversity based on channel coding methods, the capacity of wireless erasure networks, and the esign and analysis of iterative-decoded communication systems operating at very low bit and frame error rates.

Embedding computational intelligence in robotic and critical infrastructure systems will revolutionize how we live our lives. The spark for this revolution can be seen in smart grid, intelligent supply chains, and self-driving vehicles. Research in Intelligent Robotics and Infrastructure focuses on soft robotics, multi-robot cooperative tasking, advanced manufacturing systems, and human machine collaboration, and smart city applications. Many of these systems may be seen as networked cyber-physical systems (CPS) that Notre Dame played a pioneering role in developing.

Notre Dame's materials research focuses on the synthesis and implementation of novel materials into state-of-the-art and emerging devices. With applications in energy-efficient integrated circuits, high-performance computing, artificial intelligence, 5G/6G/7G communications, force protection, alternative energy harvesting and storage, nanophotonics, bioengineering, and quantum computing and quantum communication, our students and faculty have a big impact on societally important technologies. With some of the best equipment for materials deposition and characterization in the country, coupled with Notre Dame’s state-of-the-art cleanroom facilities, our students make important breakthroughs in never-before-synthesized materials and unique devices with superior performance.

Research in this area designs materials, devices, circuits, and algorithms for applications in wideband, high-speed, low-power wireless communications and sensing. Current projects use device-circuit-system optimization methods, materials and analog circuits for real-time processing, and engineered materials and metamaterials for efficient beam-steering antennas. Much of this work is affiliated ND's group studying nano-scale technologies (NDnano) and Notre Dame's institute studying wireless communication and networking ( Wireless Institute).

We use nanoscale engineering to push beyond the limits of conventional electronics and photonics, exploiting quantum phenomena to create devices that interact with the world around us in extraordinary new ways. Notre Dame played a pioneering role in a transistor-less paradigm known as Quantum-dot Cellular Automata (QCA). QCA enables binary computing which can be scaled down to the single-molecule size scale. QCA has been explored in metal-dot, GaAs, Si, nanomagnetic, and molecular systems.

Research in this area focuses on high-performance electronic devices and circuits across a range of emerging and high-performance materials (e.g. III-Vs such as InP, GaAs, InAs, AlGaSb; III-Ns including GaN, AlGaN, ScAlN; 2D materials such as transition metal dichalcogenides, and more). The group does work within the areas of advanced fabrication processing and device demonstration, supported by efforts in device design and simulation, characterization, and modeling. Much of this work is collaborative work between the colleges of Science and Engineering to address issues regarding nano-scale technology.

The Notre Dame Nanophotonics Group focuses on optical materials and devices that emit, detect, and control optical fields. Our interests include metamaterials and metasurfaces, optically-addressable defects in semiconductors, intersubband devices, localized and propagating surface polaritons, mid-infrared intersubband lasers, deep-ultraviolet interband lasers, and more.

Research in this area seeks to create the next generation of noninvasive biomedical imaging instrumentation and sensors that are based upon the interaction of light with biological molecules, cells, and tissue. Current work seeks to develop new technologies for higher resolution, speed, depth, and sensitivity while understanding how light interaction with chemical species can yield both physiological and quantitative information.