Research

Communications, Networking, and Information Theory (CNIT)

Research programs led by ECE faculty on all aspects of wireless communications and networking, including information theory, coding theory, applied probability theory and optimization, resource allocation, performance modeling and queueing theory, scheduling and distributed computation, security and privacy in communications, distributed machine learning and federated learning, machine learning in communication systems, and information-theoretic methods for machine learning.

Signal Processing and Machine Learning (SPML)

Research programs led by ECE faculty on all aspects of signal processing and machine learning, which include statistical and adaptive signal processing, stochastic processes, optimization, artificial intelligence and machine learning, image processing and computer vision, speech and audio processing, computational neuroscience, neural signal processing, information security and forensics, multimedia and video processing, algorithmic fairness, explainability and interpretability, robustness and adversarial machine learning, privacy, and reinforcement learning.

Control, Robotics, Autonomy, and Learning (CRAL)

This broad area is addressing in a balanced manner both theoretical foundations and significant high impact applications in dynamical systems, multi-agent decision-making, intelligent control, dynamic planning, feedback, adaptation, robustness, and learning. Principles and algorithms of optimization, dynamic games, formal methods, integration of logic and optimization, temporal logic, networked control systems, cyber-physical systems, hybrid dynamical systems, interrelationships between dynamical systems and control with AI and ML are investigated. Applications include autonomous vehicles, robotic manipulators, human-machine collaboration, trustworthy autonomy, collaborating UGVs and UAVs, control of swarms, security and privacy in control, learning enabled control, smart grids, sensor and communication networks, social networks. 

Computer Architecture (CMAR)

Computer Architecture (CMAR) is the sub-discipline within Computer Engineering that addresses how computer hardware is organized at the chip and system levels. Computer architects consider both application requirements as well as technology constraints in order to develop hardware designs that achieve the best performance, power, area, and/or productivity.  As conventional silicon-based technology scaling ("Moore's Law") draws to a close, computer architecture will become even more important in enabling future power efficiency gains. This will occur through innovations in areas such as parallelism, specialization, and new computational models.

Embedded and Cyber Physical Systems (ECPS)

Embedded and Cyber-physical systems (ECPS) are closely related areas that involve the interface between computer engineering and areas of electrical engineering, including communication, signal processing, machine learning and control. Embedded systems are computing systems that are designed for specific applications and are typically encapsulated as subsystems within larger systems. Cyber-physical systems integrate sensing, computation, control, and communication to enable knowledge extraction from and manipulation of physical processes. ECPS concepts and methods play a major role in the research and development of many important types of devices and systems, including those involved in Internet of Things (IoT), and artificial intelligence at the network edge.

Cybersecurity and Cyberprivacy (CYSP)

Cybersecurity and Privacy is the area that focuses on protecting computer systems and their users against all cyber threats, present and future. Research thrusts include, but are not limited to, software and hardware security, data privacy and integrity, cryptography, the security of distributed and cyberphysical systems, and trustworthy AI. 

Quantum Technologies (QUTE)

Quantum technologies have the potential to revolutionize a wide array of fields by exploiting the unique properties of quantum mechanics and quantized particles to achieve unprecedented levels of computational power, communication security, and sensing precision.  This subdiscipline includes the diverse fields of quantum communications and networking, quantum optics, quantum sensing, quantum algorithms, and quantum computing and simulation, as well as the quantum materials and devices that are critical for these fields.

Applied Physics and Electromagnetics (APHE)

This subdiscipline encompasses a variety of research areas at the boundary between engineering and physics, including electromagnetic materials, magnetics and spintronics, bioelectromagnetics, nonlinear dynamics, plasma physics, and vacuum electronics.  Applied electromagnetics also covers microwave systems, antennas, wave propagation and scattering, metamaterials and metasurfaces.

Optics and Photonics (OPTP)

Electronic Materials and Devices (ELMD)

The Electronic Materials and Devices research area is at the forefront of microelectronics research, focusing on the synthesis, characterization, and modeling of novel 2D, semiconducting, and quantum materials, as well as their integration into cutting-edge devices. Exploiting the unique electrical, optical, and structural properties of these materials, next-generation microelectronic devices are explored for applications including quantum computing, novel sensing technologies, photonic and plasmonic devices, and novel memory and computing paradigms. Research in this area bridges the gaps between material synthesis, novel material properties, device fabrication, and systems integration to overcome the limitations of current technology.

Power Electronics, Solid State Circuits, and Bioelectronics (PECB)

The Power Electronics, Solid State Circuits, and Bioelectronics research area is centered on advancing circuits and systems, with a keen focus on power electronics involving high-power and high-frequency devices, solid-state circuits encompassing a broad spectrum of analog and digital integrated circuits, and bio-inspired technologies like neuromorphic systems. Additionally, the research extends to the development of bio-compatible devices aimed at revolutionizing healthcare technology through the integration of these diverse areas. This research in this area combines the rigor of electrical engineering with the innovative potential of bioelectronics to create next-generation solutions.