Imaging and other sensing modalities are increasingly key to science, medicine, engineering, and many other fields, and hence computational methods for processing and extracting information from sensor data are of critical importance. Extracting useful information from raw, noisy data involves a wide range of mathematical techniques including inverse problems, optimization, modeling and prediction, discrete algorithms, and methods for high-level image understanding. At CAM, researchers are designing algorithms for a range of applications, from studying bird and insect flight, to reconstructing volume data from medical scans, to reconstructing 3D geometry from 2D images.