My research interests fall broadly into the following categories:

  • Open symbol space induction & incremental acquisition
  • The Morpho-syntactic boundary
  • Most Basic Cognitive operations as informed by linguistics
  • Segmentation boundaries and the syntactic implications
  • Computational, Logical, and representational limitations of Neural Networks, or really all probabilistic models
  • Tree transduction
  • Astronomy
  • Optics
  • Hardware & Mechanical Engineering
  • Education policy
  • More biologically speaking:
    I am interested in those things that allow me to see and think with more detail.
    … probably because my vision is innately bad.

    Python OpenGL Tree Drawing

    To make a pretty output for my distributed web crawlers, I wrote this happy 3D tree module for python. It is OpenGL, and makes use of the brilliant visual python opengl module. You can see the tree output at the left as controlled by the crawlers. This module takes care of placement and frame management of the branches and all of their…

    Compressing to 15 minutes

    Here I provide a hyper-brief overview of what causality is, provide insight on the limitations of probabilities, and illustrate some results of causal induction. I also misspeak a lot; I don’t like talking, much less talking quickly. i.e. ‘Joy Christianson → ‘Joy Christian’

    3D Tree/Edge Relation Graphing: ‘Semantic’ Maps of Word-Content Relations

    Using our massive dataset (16GB) of hierarchical relations, we attach the decomposed trees in an OpenGL 3D framework to determine what sorts of structured content-relationships emerge (if any) in the graph. I’ll be uploading a version of the code for people to play with (if they want to) shortly…

    Dissertation Progress: Part I

    Alright, rather than actually work on my dissertation, and since I’ve all of a sudden become such an avid blogger, I thought that I’d blog on my progress! Currently I’d estimate the overall document to be about 66-70% done, currently at about 120pgs. It has 6 chapters, of progress levels: Chapter 1: 98% Chapter 2: 98% Chapter 3: 60% Chapter 4: 56%…

    Statistical Learning is not “Learning”

    New techniques are named to provide an intuition of their process.  All techniques built upon it are colored by the original terminology.  In time, those techniques come to color the terminology itself, slowly supplanting the original meaning with the new one. Introduction Sometimes a discussion about word usage is an irrelevant exercise of ego.  Other times, word usage becomes very important, as…