Stochastic Computing

Understanding the brain behavior is currently gaining a huge attention worldwide. At the sensors lab, students under the supervision of Prof. K.N. Salama are exploring new computing technologies miming the way our brains process and store data. Using memristors to build neural networks reduces the required area significantly compared to classical circuits. ReRAM have also gained a lot of interest. Resistive memory devices are very promising candidates replace the current storage technologies, due to their very high density, fast access time, and retainability. However, there are numerous challenges that need to be addressed before memristor devices genuinely replace the current technologies. The student will get access and training during their research at state-of-the-art experimental labs, advanced nano fabrication and characterization lab, supercomputing and visualization facilities. Student Qualifications: Strong Background in electronics, physics, computer science, computer engineering Good communications and presentation skills Willingness to travel to work with international collaborators Knowledge of SW tools like scripting languages (Python), Matlab, 3D Max, Google Sketch.