Abstract.  Advances in the understanding of and ability to model the human lungs have resulted in computational methods that allow researchers to investigate the structure-function relationship of pulmonary airflow in the lungs. However, accurate and subject-specific computational models are time-consuming even when parallelized to run on supercomputing clusters. Reducing the runtime of such models is essential to allow researchers a practical and efficient means for conducting large-scale population studies. Graphics Processing Units (GPUs), more familiarly known as the video cards in computers and gaming systems, have emerged as a powerful and affordable tool for many applications in engineering and scientific computing. In this talk, after a brief overview of GPU computing, I will discuss the use of GPUs and methods designed to accelerate performance for various components of our digital lung model, such as image registration and particle tracking methods, as well as exciting possibilities for real-time visualization of simulation results using augmented reality. Time will be reserved during the talk for discussion of possible topics/questions about the upcoming stages of graduate studies, such as what you can do now to make life easier when thesis writing, job searching, finding an adviser, etc.