Our world is full of signals, some of which we see and others which are invisible. These signals range from WiFi signals to brain waves. The pervasiveness of these signals results in networking the world through natural and man-made links. The aim of the Signals Kinetics group is to program these natural and man-made networks in order to extend human and computer abilities in communication, sensing, and actuation. We draw on tools from computer networks, signal processing, machine learning, and hardware design to uncover, analyze, and engineer these networks.
Students and postdocs with strong technical backgrounds in computer science, electrical engineering, and/or physics. Background in computer networks, signal processing, machine learning, computer vision, HCI, and/or hardware design is desirable but not required. A portfolio is not required (or useful) for admission into the group.
