Title: Noisy Group Testing and Boolean Compressed Sensing In this talk we will motivate group testing from examples drawn from communications and biology. We will then formulate a noisy version of the group testing problem and draw analogies to the compressed sensing problem. Our noisy version accounts for both false positives and missed detections. We will present information theoretic upper and lower bounds to obtain tradeoffs between noise, number of tests, sparsity, group size and distortion in some interesting cases.