I am interested in computer vision and machine learning. Specifically I work on fine pose estimation, prediction from rendered data, deep learning, and fine-grained classification. My research focuses on automatically generating large scale data sets for training computer vision algorithms. It is common knowledge by now that we are living in an age of "Big Data". However, while data is cheap labeled data is not. Building large scale labeled datasets is time consuming and expensive. In my research I leverage the large quantities of highly accurate, detailed, 3D models that are readily available on sites such as turbosquid.com to create rendered images as training instances for computer vision tasks. This provides a complete solution to the problem of curating labeled data. Please see my Publications section for my thesis.