I am a graduate student in MIT CSAIL, studying machine learning and computer vision with Bill Freeman. Previously, I received a B.S. in symbolic systems and an M.S. in computer science from Stanford University, and my advisor was Andrew Ng.
The human brain analyzes the sensory world by building a hierarchy of representations, where each layer captures increasingly high-level and abstract structure. One interpretation is that the role of each layer is to take structure which is only implicit in lower layers and make it explicit. With this inspiration, my research has focused on learning mid-level representations which make explicit various features of the environment. This work draws upon techniques from a number of areas, especially deep learning, Bayesian statistics, and image processing. Specific topics I’ve worked on include:
Room 32-D466, Stata Center
Massachusetts Institute of Technology
32 Vassar Street, Cambridge MA 02139