A Digital Cure for Epilepsy
Faculty Project Leader: Behnaam Aazhang
Epilepsy is the 4th most common neurological disease in United States. Unfortunately 30% of the patients don’t respond well to traditional treatment like drugs. For those patients, the only permanent treatment is resection of the part of the brain whose hyperactivity is responsive for seizure. This method is invasive and carries high risk. Thus, reliable alternative treatment is needed. By predicting seizure before its onset, doctors could act preventively with actions that include stimulation treatment recently proposed.To facilitate that, scientists at Rice University and the University of Texas Health Science Center will work together to develop algorithms that will optimize the development of an implantable device. The device will deliver low-frequency electrical stimulation to the seizure on-set zone. Once the prototype is developed, the group would pursue clinical trials.
Digital Gym
Faculty Project Leader: Ashutosh Sabharwal

Imagine a gym that helps you keep track of your exercise, its intensity, its correctness and your vitals while you focus on exercise. Automatically. Accurately. Even without a wearable. Every time. Welcome to the Digital Gym. We are developing technologies that will convert any gym into the digital gym of the future. Digital Gym is a project in the world’s first Quantified Communities (QC) movement launched by Rice Scalable Health Initiative.

DISSECTDIStrubuted Sensors, Effectors and Computers Team
Faculty Project Leader: Ray Simar
The game of golf has existed in its modern form since the 15th century…and one club stands alone: the putter. About half of the shots in golf are made with the putter. Putting is not easy – the putter swings slowly, and with a very light force. It is incredibly challenging and frustrating. Even professional golfers often miss short putts. The DISSECT team aims to provide feedback to the golfer, so that they can learn to precisely control the magnitude of force that they apply to the golf ball.
Parallel Hardware Applications in Science and Technology (PHAST)
Faculty Project Leader: Joseph Cavallaro
Recent advances in VLSI technology are enabling fast computing systems with tens and hundreds of processing units. These range from field programmable gate arrays (FPGA) to graphics processing units (GPU) to multi-core processors, such as the Intel Xeon Phi. These parallel systems can be used to accelerate applications in wireless communications, image processing, and data science. Current projects focus on signal processing algorithms for 5G base stations for large scale or Massive MIMO wireless communications systems. Parallel programming environments and software tools such as CUDA, OpenMP, OpenCL, and MPI are used on systems from mobile GPU system-on-chip devices (SoCs), to high performance desktop GPUs to supercomputers at the Texas Advanced Computing Center.