| Simulation Neuroscience Cells and Neuromathematics
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Lida Kanari is the Group leader for the Cells and Neuromathematics group in the Simulation Neuroscience Division.
Lida leads a team of 8 scientists who oversee the development of computational tools to study the structural and functional properties of single cells in the brain. She is currently developing techniques to study the differences between species, such as mouse, rat, and human. She is also investigating the mathematical links between neuron morphology and network topology to study the biological mechanisms of network formation. Topological data analysis (TDA) leverages algebraic topology to analyze data, significantly impacting fields like protein studies, cancer detection, material science, and brain networks. In her thesis, Lida used TDA to include tree structures, creating the Topological Morphology Descriptor (Kanari et al. 2018), which can accurately classify and cluster neuronal morphologies, and analyze vascular networks, astrocytes, and microglia. Generative models of neurons are essential for understanding brain networks and simulations but struggle to generalize across datasets. Lida addressed this by developing an inverse TDA approach (Kanari et al. 2022), generating trees that are statistically similar to biological neurons, leading to the first topological synthesis algorithm. Lida has an MSc in Applied Mathematics and Physics and an MSc in Computational Fluid Mechanics from the National Technical University of Athens, Greece. She was awarded a PhD from EPFL in Computational Neuroscience for her thesis on “Neuronal morphologies: the shapes of thoughts”. Apart from scientific research, Lida is interested in theater, music, movies, photographs and books. She also enjoys hiking, biking and kayaking in the Greek and Swiss mountains. Awards2018 2017 2011-2012 2006-2011 2009-2010 2003-2005 Selected Publications2022 2022 2020 2019 2018 |
