Digital Signal Processing Group
Digital Signal Processing (DSP) — the transformation of data to extract or better transmit information — has evolved from an obscure research discipline into an essential technology of everyday life. Rice has been a major force in DSP research and education and many outstanding DSP alumni now hold leadership positions in academics and industry.
Associated Faculty: Baraniuk, Burrus, Cavallaro, Frantz, Johnson, Kemere, Orchard, Patel, Pitkow, Sabharwal, Veeraraghavan
Laboratory for Nanophotonic Computational Imaging and Sensing
The laboratory for Nanophotonic Computational Imaging and Sensing (NCIS) designs and builds imaging systems that can dramatically outperform systems built from traditional physical optics. The founding principle is that by co-designing nanophotonic devices and imaging algorithms, we can break free of the limitations imposed by conventional physical optics like lenses and mirrors.
Associated Faculty: Robinson, Veeraraghavan
Luan Laboratory of Integrative Neural Interface
The Luan Laboratory of Integrative Neural Interface research focuses on the development of multimodal neural interfaces that combine the state-of-art electrical, optical and other technologies to monitor and manipulate brain activity. The application of these neurotechnology advancements enables the fundamental investigation of neurological disorders and the development of novel therapies. The lab aims to develop tools to create a multifaceted picture of the brain in health and in disease, and to seek new ways to better diagnose, treat, cure, and even prevent brain disorders.
Nanoscale Neural Interface Laboratory
Nanoscale Neural Interface Laboratory (Xie Lab) develops theories focused on tissue integrated neural electrodes, neural recoding, neural interfaces, and longitudinal electrophysiology in clinical research.
Associated Faculty: Xie
Neural Computation Laboratory
The Neural Computation Laboratory aims to understand how the brain works using mathematical principles. They develop theories of neural computation and collaborate with experimentalists to test these predictions.
Associated Faculty: Pitkow
Patel Lab
Ankit Patel's Lab is a part of Rice Neuroengineering. Patel's focus is to bridge neuroscience and deep machine learning, by building theories that work in the real world.
Associated Faculty: Patel
Realtime Neural Engineering Laboratory
The Realtime Neural Engineering Laboratory focuses on forming, storing, and using memory in the hippocampus. Problems in the hippocampal circuit can lead to memory problems (e.g., Alzheimer's, PTSD) and also more complex disorders such as depression and anxiety. We'd like to understand how the hippocampal circuit works at a systems-level in healthy brains, how it goes wrong, and what can be done to change how it functions.
Associated Faculty: Kemere
Robinson Lab
The Robinson Lab for Nano-neurotechnology believes that new methods to measure and manipulate the activity of specific brain cells will reveal fundamental principles of brain function and advance the treatment of neurological disorders. Using semiconductor nanofabrication and genetic engineering, the lab creates electronic, photonic, and magnetic interfaces to the brain. In addition, the lab studies millimeter-sized invertebrates with tiny nervous systems. By creating interface technologies for these tiny organisms, the lab hopes to decode the activity of the entire nervous system and uncover how simple brains operate to solve complex problems.
Associated Faculty: Robinson
Laboratory for Noninvasive Neuroengineering
The team in the Szablowski Lab for Noninvasive Neuroengeeirng are developing technologies for noninvasive control and monitoring of the brain. In our work, we combine synthetic biology, molecular engineering, and strategies for enhanced gene and drug delivery into the central nervous system. Their goals are to understand neural circuit function and treat brain disorders with fewer side effects.
Associated Faculty: Szablowksi
Translational Biomimetic Bioelectronics Lab
The TBBL is part of two large neuroengineering initiatives, one at UTHealth and one at Rice University. Dr. Seymour and his team focus on the advancement of neurotechnology for improved treatment of neurological disease. They are dedicated to answering the many questions that remain about how to improve the efficacy of implantable devices currently being used to treat conditions such as epilepsy, aphasia, locked-in syndrome, and ALS.