Conventional computing based on Von Neumann architecture approaches its limits in scalability and power consumption.
If solved with contemporary machines, today’s applications in science and industry related to data analysis, pattern recognition and prediction would demand a huge computing power. In the era of ubiquitous sensing and data acquisition, a way to cheaply and power efficiently make sense of the collected ‘big data’ is of utmost importance. Here, human brain’s efficiency becomes the ultimate standard and inspiration for any future technology. Such trend of 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.