Griffiss

Software Defined Radio and Machine Learning for Exploitation (Internship)

The AFRL/RI SIGINT (Signal Intelligence) Group would like to transform the traditional methods for encoding, modulating, transmitting, receiving, exploiting, demodulating and decoding the information carried by man-made signals. We are looking for smart, low complexity, efficient, real-time, reliable and multifunctional transceivers and techniques that take advantage of novel signal processing and machine learning methods. We are also interested in extending methods beyond their conventional usages. Typical summer projects include classification, detection, estimation, classification, coding, and other areas of telecommunications applied to hostile and complex environments. The projects are designed to promote brainstorming and allow the student to implement guided solutions or propose and develop their own depending on technical merits.