Research
Embedded Systems and Machine learning
RICE CE has extensive research in embedded system and machine learning powered Internet-of-Things. Research is focused on making edge-devices intelligent through novel machine-learning techniques, audio and computer vision systems, and ultra-small computing to open up new application domains.
Research Labs
Towards bringing powerful machine-learning systems to our daily-life devices, the Efficient and Intelligent Computing (EIC) Lab at Rice University explores techniques that highlight a holistic optimization of algorithm-, system-, and application-level opportunities.
Rice computational imaging lab focuses on solving hard and challenging problems in imaging and vision by co-designing sensors, optics, electronics, signal processing, and machine learning algorithms. This emerging area of research is called computational imaging or more generally computational sensing. Our group is generally application-agnostic and focuses on developing foundational theories, tools, techniques, and systems.
Professor Cavallaro, in collaboration with Professor Behnaam Aazhang, is developing parallel architectures for code division multiple access (CDMA) wireless communication systems. This involves the use of parallel arrays of DSP/FPGA processors and custom VLSI processor architectures.
We design systems to interact with complex neural circuits in vivo in behaving rodents. These systems enable us to explore how information is processed, stored, and retrieved in both healthy brains and in models of human neurological diseases and disorders. The experimental neurobiological topics we focus most on are understanding memory and the mechanisms of deep brain stimulation. Additionally, we do a signicant amount of pure neural interface technology development as well as building software and embedded tools for data analysis and experimetns.
RICE CE has extensive research in embedded system and machine learning powered Internet-of-Things. Research is focused on making edge-devices intelligent through novel machine-learning techniques, audio and computer vision systems, and ultra-small computing to open up new application domains.