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akilgall/README.md

Hi, I'm Aaron, a 6th year graduate student studying Physics at the University of Oregon. Here are some highligted software projects that I have designed and implemented.

Highlighted Machine Learning Project

My thesis work involves utilizing machine learning techniques such as unsupervised learning to search for exotic dark particles produced at the Large Hadron Collider. An example of this method is in the CWoLa repository! While real analysis data can't be released from LHC experiments, an example of this method as applied to toy pseudodata works equally well for demonstrating the power of this method.

autoTriangulation

A software project of mine that is currently used in production is called autoTriangulation (LPSC Abstract). Digital Terrain Models (DTMs) are created from stereoscopic images and pixel-matching is used to derive the terrain elevation in a relative sense. These DTMs are then adjusted with respect to fixed laser altimetry to given an absolute calibration of the terrain. This triangulation relative to the altimetry is traditionally done manually, however, this program allows this lengthy step to be automated for a majority of terrain scenes. The original software and algorithm was written in MATLAB but was translated to an installable software by a dedicated coder (User Manual).

Popular repositories Loading

  1. akilgall akilgall Public

    Config files for my GitHub profile.

  2. CWoLa CWoLa Public

    A demonstration of the Classification Without Labels (CWoLa) method on toy datasets to search for exotic particles.

    Jupyter Notebook

  3. RingNN RingNN Public

  4. NeuronalModeling NeuronalModeling Public

    A framework illustrating some neuronal modeling of single particles as well as machine learning aspects to track segmentation.

    Jupyter Notebook

  5. DLGemmaForDiffusion DLGemmaForDiffusion Public

    Python

  6. CytoCommunity CytoCommunity Public

    Forked from huBioinfo/CytoCommunity

    A spatial omics data analysis tool that enables both unsupervised and supervised discovery of complex tissue cellular neighborhoods from cell phenotypes.

    Python