C. Braxton Owens
Confidence without doubt is the fastest path to being dangerously wrong. - me
Currently, I am a PhD student at BYU working in the Biophysics group. I have the privilege of working with wonderful scientists like Grant Jensen, Bryan Morse, and Gus Hart on a daily basis. I love linear algebra and its applications, I live in the terminal with neovim, and my favorite textbook is High-Dimensional Data Analysis with Low-Dimensional Models: Principles, Computation, and Applications, which I just call “High-Dim, Low-Dim.”
I am a believer in open collaboration and am grateful for the community of open-source developers who make my life better.
I am currently conducting research in computational cryo-ET, using both classical and deep ML methods to identify low-signal macromolecular complexes in tomograms. This research allows us to achieve the near-atomic scale resolution needed to understand fundamental life processes.
On a more personal note, I love to read fantasy, snowboard, and teach my three sons that it was actually Leibniz, not Newton, who invented calculus.
news
| Oct 19, 2026 | Our paper “A Dataset and Competition to Automatically Find Flagellar Motors” was accepted to Communications Biology! 🎉 |
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| Oct 15, 2026 | Our paper “POPSICLE: Benchmark Datasets for Segmentation and Localization in CryoET” was accepted to WACV 2027! |
| Sep 01, 2026 | Wrapped up a summer internship as a Machine Learning Engineer Intern at Adobe in Lehi, Utah. |
| Sep 03, 2024 | Website created!! |
latest posts
| Sep 03, 2024 | Segment Anything Model Applied to CryoET |
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selected publications
- Feature Engineering Descriptors, Transforms, and Machine Learning for Grain Boundaries and Variable-Sized Atom Clustersnpj Computational Materials, Jan 2025
- A Dataset and Competition to Automatically Find Flagellar MotorsCommunications Biology, Oct 2026In press