I am a Postdoctoral Associate in the Yale Department of Radiology & Biomedical Imaging. I work in the Image Processing and Analysis Group (IPAG) with Professor James Duncan and Professor Kevin Pelphrey.
My research lies at the intersection of multimodal integration, network modeling and clinical neuroscience. I believe that we are fast approaching the limit to what we can learn about the brain from a single modality or paradigm. Hence, the future of medical research will require a system viewpoint that leverages complementary sources of information to fully describe each neurological impairment. By combining analytical techniques, such as probabilistic modeling and network theory, with neuroscientific findings, my goal is to understand and characterize complex processes within the brain. My work promises to yield new insights into debilitating neuropsychiatric conditions, such as dementia, traumatic brain injury and autism, with the long-term goal of effecting patient treatment and care.
I completed my PhD in August 2012, under the supervision of Professor Polina Golland at MIT. My PhD thesis investigates generative models of brain connectivity. In contrast to traditional imaging, brain connectivity analyzes the interactions between regions. Such relationships inform us about patterns of neural communication as well as the structural/functional organization of the brain. My thesis tackles two challenging problems in the field: (1) multi-modal analysis of functional MRI and diffusion MRI data, and (2) localizing impairments of a neurological disorder based on global connectivity patterns. Here, I rely on probabilistic graphical models to capture hidden and observed interactions within the brain.
I earned my B.S. (2006) and M.Eng. (2007) in Electrical Engineering from MIT. My M.Eng. thesis was supervised by Professor Alan V. Oppenheim; it explores a novel method for signal approximation that is based on an anti-aliasing frequency warping.
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