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  • Rossi Lab @ UBC

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ian-coccimiglio/README.md

Table of Contents

  1. I’m currently working on the following scientific and software-development projects:
    1. Clonal Dynamics of Regenerating Muscle Stem Cells
    2. Semi-Automated Muscle Fiber Imaging Platform
    3. Mapping Exercise Training To Exercise Performance

Hey there, you’ve found the place where you can figure out who I am.

I’m completing my Masters in Biomedical Engineering at the Rossi Lab at the University of British Columbia. I’m a long-time coach, occasional marathon runner, and computational biologist.

My technical software background.

  • Worked in Windows through my undergraduate, moved to Linux in 2020 (with some Mac). Most worthwhile technical choice I’ve ever made.
  • I use Manjaro (btw). Still not cool enough to be with the Arch crowd.
  • I started learning vim editing in 2021, but I was compelled to try Doom EMACS in 2023. Now I believe any editor can improved with Vim key-bindings, even CRISPR.
  • I’m now working in the realm of biological imaging and statistical analysis, mixed in with practicing machine learning using Python.
My software familiarity Technologies/Tools
I love these and use them regularly Python, R/RStudio, Tidyverse, Vim, DOOM Emacs, Linux, Manjaro, Spyder, VScode, Fiji/ImageJ, Bash, Shell-scripting, Conda, AUR, Org-mode
I like these and use them when appropriate Jupyter, HTML, Jython, Mac, Git/Github, Wordpress, ImageJ Macro, Napari, Tk/Tcl, Graphpad, Hugo, AWK
I’m learning more about these Tensorflow, Torch, Scikit-learn, Java, Rust, Lisp, Probablistic Programming (Blang/Stan), HTML/CSS, SQL
For better or worse, I know these MATLAB, Windows, MS Office

I’m currently working on the following scientific and software-development projects:

Clonal Dynamics of Regenerating Muscle Stem Cells

[Project: Transposon-Tracking] Leveraging Bayesian statistics to gain insight into muscle-progenitor renewal.

Semi-Automated Muscle Fiber Imaging Platform

[Project: Lightning-Fiber] A fast Fiji-based platform which addresses the vexing problem of quickly imaging, segmenting, and measuring muscle fibers. Developed with direct biologist input.

Mapping Exercise Training To Exercise Performance

[Project: Delta-Performance] The goal of coaching has always been to find the most effective ways to train.

Popular repositories Loading

  1. napari-easy-augment-batch-dl napari-easy-augment-batch-dl Public

    Forked from True-North-Intelligent-Algorithms/napari-easy-augment-batch-dl

    A plugin for deep learning labeling, augmenting, training and predicting on 2d image sets. Well suited for training specialist networks using a small number of labels.

    Python 3

  2. iconda iconda Public

    Lightweight GUI to create desktop icons that can manage conda/mamba environments

    Python 2

  3. SAMLab SAMLab Public

    Generating label images from SAM predictions

    Jupyter Notebook 1

  4. napari-segment-everything napari-segment-everything Public

    Forked from True-North-Intelligent-Algorithms/napari-segment-everything

    A Napari SAM plugin to segment everything in your image (not just some things)

    Python 1

  5. skeletal_muscle_toolbox skeletal_muscle_toolbox Public

    Distributing macros for scientific skeletal muscle imaging in ImageJ and Fiji.

    ImageJ Macro 1

  6. I2K_Deep_Learning_For_Biological_Segmentation I2K_Deep_Learning_For_Biological_Segmentation Public

    Developing a Workflow for Biological Instance Segmentation

    Python 1