Building on more than three decades of research successes, a major goal of our research program is to prove, encourage, and support new and far-reaching initiatives that look 10+ years into the future. Driven by a core group of internationally recognized faculty, extensively and uniquely experienced in research and education, our culture fosters close collaboration, which is the major force that maximizes technology impact and direction. Through various funding programs, Rice has been able to demonstrate leadership in focused research initiatives: Computer Engineering; Data Science; Neuroengineering; Photonics, Electronics and Nano-devices; and Systems.
The research in this discipline focuses on many different aspects and touches on virtually every area that CE encompasses. Analog and mixed signal design, including self-healing circuits and large-scale radiating integrated circuits for medical imaging. Computer architecture and embedded systems, like those in biosensors and mobile wireless healthcare and parallel computing for data science algorithms, large-scale storage systems, and resource scheduling for performance, power and QoS. Hardware security and storage, such as the security schemes which are being based on physically unclonable functions. VLSI signal processing focuses on algorithms for wireless communication systems and their efficient mapping to low-power architectures on DSPs, GPUs, ASICs, and ASIPs. Last but not least is biosensors and computer vision — smartphones with imaging devices are leading to new areas in computer vision and sensing.
Data Science is an emerging discipline that integrates the foundations, tools and techniques involving 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. They get to the questions at the heart of complex problems and devise creative approaches to making progress in a wide variety of application domains.
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.
Photonics, Electronics & Nano-devices
The focus of this program is the improved understanding of electronic, photonic, and plasmonic materials, optical physics, the interaction of light and matter, along with the application of that knowledge to develop innovative devices and technologies. The specific areas of interest cover a broad range: Nanophotonics and plasmonics, optical nanosensor and nano-actuator development, studies of new materials, in particular, nanomaterials and magnetically active materials; imaging and image processing, including multispectral imaging and terahertz imaging; ultrafast spectroscopy and dynamics; laser applications in remote and point sensing, especially for trace gas detection; nanometer-scale characterization of surfaces, molecules, and devices; organic semiconductor devices; single-molecule transistors; techniques for optical communications; optical interactions with random, nanoengineered, and periodic media; and applications of Nanoshells in biomedicine.
DSP, Systems & Wireless
Signal processing is the analysis and transformation of signals -- measurements taken over time and/or space -- in order to better understand, simplify, or recast their structure. Rice has a long history in digital signal processing (DSP) dating back to its inception in the late 1960s. Current research spans a wide range of areas, including image and video analysis, representation, and compression; wavelets and multiscale methods; statistical signal processing, pattern recognition, and learning theory; distributed signal processing and sensor networks; communication systems; computational neuroscience; and wireless networking. Machine Learning is a large part of our Systems Research.
The Rice ECE Health research area focuses on healthcare and wellness technologies. Projects include bio-behavioral sensing, and bio-imaging.
Faculty are dedicated to quantitatively understanding the behavior-biology-health pathways. With each innovation, they move a step closer to the vision of bio-behavioral medicine, where behavior and biology are treated cohesively and with empathy.
Research teams take advantage of being located within the Texas Medical Center area; they also work with community partners to hold “computing for health” programs for k-12 students and high school teachers.