Machine Learning/Neuroscience

During my time at the MIT CSAIL before coming to Harvard, I worked on machine learning research and on its applications to neuroimaging. On the technical side, my research involved developing novel unsupervised learning methods and, more specifically, nonparametric hierarchical Bayesian models that allow us to analyze neuroimaging data across multiple subjects. On the neuroscientific side, the main goal of my research was to discover areas in the human brain that are specialized in performing particular high level cognitive tasks. 
 
My research was published in the top machine learning publication NIPS and neuroscience publications such as Journal of Neurophysiology and NeuroImage. In 2009, I received the honorable mention for the Francois Erbsmann award from the biennial international conference on Information Processing in Medical Imaging (IPMI).
 
To find out more about my work in machine learning and neuroscience, you can see my Google Scholar profile here: Link to Google Scholar Profile