Computer Engineering is about innovating, prototyping, and demonstrating hardware and software systems for computing, communication, sensing, and storage. Advancing the performance, efficiency, security, cost, and form factors of these systems is critical for enabling future information and health technologies. Our research program spans analog/digital/mixed-signal/mmWave integrated circuits, micro-systems, VLSI and FPGA acceleration, computer architecture, and hardware/software co-design. We are particularly interested in emerging technology platforms and application domains, including but not limited to bioelectronic medicine, mobile health, Internet of Things, analog and neuromorphic computing paradigms, AI and machine intelligence, neuro-engineering, and next-G wireless.

Rice ECE is a global leader in wireless networking, ranging from fundamental theory to city- scale testbeds, and at-scale field trials. Topics of study include information theory, massive antenna arrays, autonomous drone networks, diverse spectrum access, distributed sensing and wireless security. New emerging technologies include Terahertz communications, programmable metasurfaces, machine learning frameworks and methods for network optimization, and open-source development for software-defined wireless networks.

Data Science integrates the foundations, tools, and techniques of data acquisition (sensors and systems), data analytics (machine learning, statistics), data storage, and computing infrastructure (GPU/CPU computing, FPGAs, cloud computing, security, and privacy) to enable meaningful extraction of actionable information from diverse and potentially massive data sources. Data scientists in ECE use digital signal processing and machine learning algorithms
to collect and understand the structure of data, looking for compelling patterns that tell the story that’s buried in the data. The understanding of how to analyze and restructure signals can be applied to a wide range of areas, including artificial intelligence (AI), signal and network analysis, computer vision, and computational neuroscience.

Quantum mechanics has been studied for nearly a century, providing rules that explain physical processes in atoms, molecules, and solids, leading to the invention and commercialization of lasers, MRI, transistors, and nuclear power generation. The field is now undergoing a second revolution, based on genuinely quantum, nonintuitive concepts such as superposition and entanglement that could enable even more powerful applications. We are utilizing cutting-edge
photonic, electronic, and magnetic technologies to control quantum particles and quasi-particles such as spins, photons, excitons, phonons, plasmons, magnons, and polaritons in quantum materials and devices for applications in computing, simulation, sensing, and networking.

Computer vision is at the heart of some of the most exciting technological developments that we are seeing today. Fully autonomous cars and drones were once a dream that would take an infinite amount of time and expense to become a reality. Today, such vehicles are actively under development and may be realized to a large degree by the end of the current decade. Computer vision is the key area underlying such advancements in autonomous systems. Furthermore, computer vision is driving fundamental shifts in augmented reality and healthcare systems through advanced object recognition and 3D reconstruction. Advances remain to be done through algorithm design, hardware development, and system integration.

Neuroengineers exploit engineering principles to understand, manipulate, and repair the activity of the nervous system. At Rice we develop methods to decipher and manipulate the neural code based on signal processing, machine learning, and information theory. We also develop physical devices that integrate with living tissue to precisely measure and manipulate neural activity. Rice is uniquely positioned to lead this field thanks to the broad, interdisciplinary research performed in conjunction with the Texas Medical Center, steps away from the Rice University campus.

Digital technologies hold the potential for changing healthcare from episodic care to continuous care paradigms. Simultaneously, they can be uniquely scalable to deliver healthcare to people not possible today and to provide a framework for more equitable healthcare. Our mission is to invent and translate novel sensors, new care systems, and AI-based intelligent tools to realize equitable healthcare for the future.