George Glidden 
Hi! I’m George. I joined the Wheeler lab on September 19th, 2022. I’m developing tools for de-novo peptide sequencing that integrate classical spectrum graph techniques with interpretable machine learning. I wrote a paper about a surprising effect of reversals in biosequence benchmarks, and I’m writing another on the theory of palindromes.
Previously, I was an undergraduate at the University of Montana, studying mathematics and computation. I did research on k-graph C*-algebras and two-bridge links under Elizabeth Gillaspy and Eric Chesebro, respectively. My first exposure to science was a high school internship at Rocky Mountain Laboratories under Elizabeth Fischer, Ted Hackstadt, and Adam Nock, where I developed a noise-robust edge detection algorithm.
When I’m not working, or having an existential crisis about our immanent Anthropocene extinction, I’m gardening, hanging out with my cats, walking around Tucson, and trying to create and consume as much art across as many mediums as possible.