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I am a Biophysics Theory Fellow at Princeton University. I specialize in designing mathematical and computational frameworks to understand how the brain works. During my Ph.D. at Columbia University, I developed a theory for how the brain interprets subtle sensory cues within the context of its internal experiential and motivational state to extract unambiguous representations of the external world. I also solved a problem in random matrix theory and toyed with kinetics of chemical reactions. Recently I have developed a novel statistical inference method to characterize neural responses to natural, structured, and correlated stimuli. Having trained as a physicist and engineer, the range of neuroscientific questions that interest me is broad but always faithful to the interface between the physical and the biological. My future research will continue to be interdisciplinary and make diverse impacts - from mathematics to experimental neuroscience.