Many mathematical models of biological systems have addressed only an isolated aspect of the system -- such as its biochemistry or mechanics -- and these simplified (yet not simple) models have shed much light on fundamental processes. Recently, biological modeling has now advanced to the point where integrative models that couple multiple processes are often developed. Typically, such models involve different spatial and temporal scales. Examples include models of tumor growth that couple solid mechanics with cell signaling and biochemistry and models of blood flow in the heart that couple solid mechanics, fluid mechanics, and bioelectricity. Common to these integrative models is the inclusion of experimental data that has high resolution both in time and space. The effective use of such models calls for new mathematical and numerical techniques; for instance, in the solution of inverse problems, in the derivation of more robust methods for parameter estimation, and in the determination of better numerical methods for the handling of multiscale coupling. This workshop seeks to address some of these challenges through a series of lectures and discussions.