Computational intelligence and neuromorphic computing potential for geospatial research and applications

In today's highly mobile, networked, and interconnected internet world, the flow and volume of information is overwhelming and continuously increasing. Therefore, it is believed that the next frontier in technological evolution and development will rely in our ability to develop intelligent systems that can help us process, analyze, and make-sense of information autonomously just as a well-trained and educated human expert. In computational intelligence, neuromorphic computing promises to allow for the development of computing systems able to imitate natural neuro-biological processes that will form the foundation for intelligent system architectures. This is achieved by artificially re-creating the highly parallelized computing architecture of the mammalian brain. As an interdisciplinary technology inspired from biology, artificial neural systems have been successfully utilized in many applications, such as control systems, signal processing, pattern recognition, vision systems, and robotics etc. In addition, the emerging neuromorphic computing field can also exploit the characteristic behavior of novel material systems with advanced processing techniques to achieve very large scale integration with highly parallel neural architectures for the fabrication physical architectures. This talk will focus on the technological challenges that we are seeking to overcome to enable intelligent parallel neuromorphic computing systems.