The ability of nano- and micro- scale components to autonomously and reversibly assemble on surfaces is broadly considered as an enabling process to numerous emerging technologies.  As a result, there is strong interest in understanding how thermal motion, particle interactions, external fields, and energetic templates can be optimally coupled in assembly processes to elicit desired material and device responses.  We approach this problem by understanding the equilibrium and dynamic evolution of colloidal microstructures via energy landscape models that accurately account for probabilistic configurational re-arrangements due to changes in k_BT-scale interactions including: tunable particle interactions (i.e. electrostatic, depletion, dipolar), external fields (i.e. gravity, electric), and patterned surfaces (i.e. physical, chemical, biomolecular).  Colloidal trajectories are measured in real-space and real-time using integrated evanescent wave, video, and confocal microscopy methods.  Equilibrium structures are connected to energy landscapes via statistical mechanical analyses (i.e. OZ and DFT theories, Monte Carlo simulations), and colloidal dynamics are interpreted by considering multi-body hydrodynamic interactions in theories for self-diffusion and dynamic simulations (i.e. Brownian and Stokesian Dynamics).  Findings from this work provide essential information to formally engineer (i.e. design, control, optimize) self- and directed- colloidal assembly processes on energetic patterns.