Dr Lida Kanari
PhD
Status
Research Fellow
Group of NeuroTopology
Research subgroups
Address
Mathematical Institute
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
University of Oxford
Andrew Wiles Building
Radcliffe Observatory Quarter
Woodstock Road
Oxford
OX2 6GG
Major / recent publications
Spatial continuity of neurons explains non-random network architecture.
Reimann, MW, Egas Santander, D, Kanari, L and Barros-Zulaica, N. iScience volume 29 (2026)
Temporal topology provides an interpretable framework for neuronal morphogenesis.
Temporal topology provides an interpretable framework for neuronal morphogenesis.
Rigaux, K, Castro A and Kanari, L. Neuroinformatics volume 24 (2026)
Open Positions
Open to PhD students to work on:
- Topological Data Analysis
- Machine Learning and AI
- Applications of mathematics on neuroscience.
One PostDoctoral Position to be announced in 2026.
See more details here!
Teaching
Further details
I am a Research Fellow of Applied Mathematics at the University of Oxford. I lead the NeuroTopology group, which is dedicated to exploring how topology and applied mathematics can shape the future of neuroscience. Combining Topological Data Analysis, Machine Learning and Camputational Modeling, we study the properties of brain morphologies with the objective to understand pathologies and improve diagnostic tools.
Highlighted publications
Of mice and men: Dendritic architecture differentiates human from mouse neuronal networks.
Kanari, L Shi, Y Arnaudon, A Barros-Zulaica, N Benavides-Piccione, R Coggan, J DeFelipe, J Hess, K Mansvelder, H Mertens, E Meystre, J Perin, R Pezzoli, M Daniel, R Stoop, R Segev, I Markram, H de Kock, C iScience volume 28 issue 7 112928 (18 Jul 2025) doi:10.1016/j.isci.2025.112928 Generating brain-wide connectome using synthetic axonal morphologies.
Petkantchin, R Berchet, A Peng, H Markram, H Kanari, L Nature communications volume 16 issue 1 6611 (18 Jul 2025) doi:10.1038/s41467-025-62030-3 Computational Generation of Long-range Axonal Morphologies.
Berchet, A Petkantchin, R Markram, H Kanari, L Neuroinformatics volume 23 issue 1 3 (10 Jan 2025) doi:10.1007/s12021-024-09696-0 A tool for mapping microglial morphology, morphOMICs, reveals brain-region and sex-dependent phenotypes
Colombo, G Cubero, R Kanari, L Venturino, A Schulz, R Scolamiero, M Agerberg, J Mathys, H Tsai, L Chachólski, W Hess, K Siegert, S Nature Neuroscience volume 25 issue 10 1379-1393 (30 Sep 2022) doi:10.1038/s41593-022-01167-6 Computational synthesis of cortical dendritic morphologies.
Kanari, L Dictus, H Chalimourda, A Arnaudon, A Van Geit, W Coste, B Shillcock, J Hess, K Markram, H Cell reports volume 39 issue 1 110586 (Apr 2022) doi:10.1016/j.celrep.2022.110586 Research interests
- Topological Data Analysis
- Algebraic Topology
- Stochastic Processes
- Computational Neuroscience
- Networks
- Machine Learning
Prizes, awards, and scholarships
Research Grants
2024 – UKRI / MRC Research Grant Algebraic topology bridging the gap between single neurons and networks
Online talks
2025 – Geotop seminar
2025 – BrainNet