I did and do a lot of stuff. My repos are a collection of tools I developed to understand and interpret high-dimensional data, and of specific projects using these tools for analysing single-cell data. The highlight is TopOMetry, an extensively documented toolkit for multiple topological and spectral analyses.

• TopOMetry, a comprehensive toolkit for high-dimensional data analysis. TopOMetry learns similarity graphs, estimates the dimensionality of the data, obtains latent dimensions using topological operators, clusters samples and layouts topological graphs into two-dimensional visualizations. The toolkit can also learn and evaluate dozens of possible representations so that users do not have to stick with any pre-determined model (e.g. t-SNE or UMAP). It includes functions to plot three-dimensional and non-Euclidean representations, and functionalities to estimate the distortion induced on latent spaces. TopOMetry was designed to be compatible with a scikit-learn centered workflow, as most classes and functions can be pipelined. The manuscript is freely available at BioRxiv.

I'm currently a postdoc at Ana Domingos' lab at the University of Oxford. My aim is to provide a molecular, neuroanatomical and functional characterisation of the sympathetic nervous system.

I'm always open to interesting conversations. Feel free to reach me by email.

I tweet about medicine, neuroscience, computational biology, machine learning, and sometimes about my personal life.