Ben Pedigo is a scientist and computational neuroengineer with eight years of experience applying statistical and software tools to nanoscale connectomes. Trained as a Johns Hopkins Biomedical Engineering PhD and NSF Graduate Research Fellow, he developed graph embedding tools (including an ASEEmbedder) as a core contributor to graspologic, now co-developed with Microsoft Research. Currently at the Allen Institute for Brain Science, he combines hands-on coding with collaborative neuroscience research—recently analyzing the first Drosophila larva nanoscale connectome. Ben’s work sits at the intersection of open-source software and reproducible neuroscience, making advanced network analyses more accessible to researchers.
9 years of coding experience
Bachelor’s Degree, Bioengineering - Applied Math Minor, Junior, Bachelor’s Degree, Bioengineering - Applied Math Minor, Junior at University of Washington
Contributions:4 releases, 677 reviews, 305 commits in 4 years 4 months
Contributions summary:Ben implemented an Adjacency Spectral Embedding (ASE) class and made minor fixes, updating documentation, and reflecting new naming conventions within the `graspologic-org/graspologic` repository. The primary focus was on graph statistics, particularly related to graph embedding, with the creation of an `ASEEmbedder` class and related methods, which demonstrates work in dimensionality reduction for graphs. The user further incorporated new functionality related to testing and comparisons using k-means.
Messing around with the CAVEclient for accessing connectome data.
Contributions:2 PRs, 236 pushes, 3 branches in 1 year
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