The Master of Electrical and Computer Engineering program at Rice University offers courses in the focus areas listed below. Highlights of the topics covered in those courses are included as well.
MECE Research Focus Areas
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Computer Engineering
Explore hardware and software as well as interactions between both. Analog and digital IC design focus on efficient machine learning implementations, cryptographic acceleration, and hardware security. RISC-V has ushered in intriguing PCB and chip design potential. The advent of smartphones and autonomous systems provides embedded systems, AR/VR, and computer architecture opportunities. VLSI signal processing focuses on algorithms for wireless systems and their efficient mapping to low-power architectures on DSPs, GPUs, ASICs, and ASIPs. |
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Wireless Systems
Invent the future of wireless by focusing on any aspect from theoretical foundations to at-scale field trials. Interact with new spectrum, new devices, and new architectures to realize ground-breaking functionality and performance. Learn and utilize tools from signal processing, network science, information theory, and random processes. Engage in the study of wireless security to ensure that communication infrastructure is resilient in the presence of adversaries that attempt to intercept or disrupt communications. |
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Data Science
Enter the emerging field of data science which integrates data acquisition (sensors and systems), data analytics (machine learning, statistics), data storage, and computing infrastructure (GPU/CPU computing, FPGAs, cloud computing, security, and privacy) in order to enable meaningful extraction of actionable information from diverse and potentially massive data sources. Data scientists in ECE use digital signal processing algorithms to collect and understand the structure in data, looking for compelling patterns, telling the story that's buried in the data. |
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Quantum Engineering
Quantum mechanics has been studied in the research community for nearly a century, providing rules that explain physical processes in atoms, molecules, and solids, which led to the invention and commercialization of lasers, MRI imagers, transistors, and nuclear power generation. Now the field is undergoing a revolution, enabling even more powerful applications, based on genuinely quantum, nonintuitive concepts such as superposition and entanglement. We are utilizing cutting-edge photonic, electronic, and magnetic technologies to control excitons, phonons, plasmons, magnons, and polaritons in quantum materials for applications in quantum simulation, quantum sensing, and quantum networks. |
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Computer Vision
Computer vision is at the heart of some of the most exciting technological developments that we are seeing today. Fully autonomous vehicles 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. Join our program to learn more about this incredible field and take part in pushing it forward through algorithm design, hardware development, or system integration. |
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Neuroengineering
The brain is essentially a circuit. Neuroengineering is a discipline that exploits engineering techniques to understand, repair, and manipulate human neural systems and networks. At Rice, we have a world-class team collaborating with Texas Medical Center Researchers to improve the fundamental understanding of coding and computation in the human brain as well as to develop technology for treating and diagnosing neural diseases. Current research areas include interrogating neural circuits at the cellular level, analyzing neuronal data in real-time, and manipulating healthy or diseased neural circuit activity and connectivity using nanoelectronics, optics, and emerging photonics technologies. |
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Digital Health
Engage in research in engineering innovations that could transform future healthcare systems. Specific current and growth areas of interest are: bio-imaging/sensing, medical imaging, multi-omics, personalized health, bio-electronics, wearables and point-of-care devices, signal processing, machine learning, control for health, AR/VR/visualization/information systems for health, and robotics for health. Research in digital health spans the spectrum from early-stage technology development to translational efforts. The faculty involved collaborate with many clinical partners nationally and have many close collaborations with the Texas Medical Center (TMC), which is the largest medical center in the world. |
