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Aurel Lazar is a Professor at the Data Science Institute of Columbia University, specializing in electrical engineering. His research interests lie at the intersection of theoretical and computational systems neuroscience, focusing on building methods for communication and networking, information theory, machine learning, and nonlinear dynamical systems. He actively engages in theoretical work aimed at developing formal methods for neural encoding, decoding, and functional identification in neural circuits. In addition, he leads projects on massively parallel emulation of neural circuits architectures, utilizing algorithms for spike domain analysis. His experimental components employ genetics and neurophysiology in conjunction with nanotechnology, particularly emphasizing neural computing engines and massively parallel neural computation. Currently, his work centers around exploring the early olfactory system of Drosophila and reverse engineering the fruit fly brain. Detailed information about his research is available through Bionet Research.
Department of Anthropology (GSAS)