Sensor networking is an emerging technology that promises an unprecedented ability to monitor the physical world via a spatially distributed network of small and inexpensive wireless sensor nodes. The nodes can measure the physical environment with a wide variety of sensors, including acoustic, seismic, thermal, and infrared. While the practically unlimited range of applications of sensor networks is quite evident, our current understanding of their design and management is far from complete. Because sensor networks collect data in a spatially distributed fashion, statistical inference problems in sensor networks present a distinct new challenge. In addition to common issues such as signal-to-noise and sampling considerations, limited energy resources place a very high cost on the sharing of data via wireless communications. Consequently, energy efficient methods for processing and communicating information play a central role in the theory and practice of sensor networks. This talk will describe "imaging" using wireless sensor networks, and discuss how recently proposed "compressed sensing" schemes may be very advantageous in such systems.