Vikranth Bejjanki’s research is concerned with examining the neural and computational mechanisms that allow humans to learn from their experiences. He uses a range of methods, including psychophysics, computational modeling, and functional neuroimaging, to study learning at multiple levels of analysis. His published work can be found in journals such as Nature Neuroscience, Proceedings of the National Academy of Sciences, PLoS Computational Biology, Neural Computation and the Journal of Vision.