Zach Claytor
Astronomical Data Scientist
Space Telescope Science Institute
I study stellar rotation and evolution using cutting-edge computational techniques. The bulk of my work uses machine learning/artificial intelligence to understand rotation of stars observed with NASA space telescopes.
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Bio
Originally from Chillicothe, Ohio, I graduated from Zane Trace High School in 2012. I have my teachers there to thank for teaching me to love learning and all things science, especially astronomy, physics, and math.
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I obtained my Bachelor of Arts in Astrophysics with a minor in Religion from Ohio Wesleyan University in 2016. Then in 2022 I obtained my PhD in Astronomy from the University of Hawaii Institute for Astronomy.
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These days I love going hiking, eating good food, and drinking good coffee.
Active Research
Using Stellar Model Grids: Kiauhoku
We run grids of models of stars to understand how they work. Rather than run a new model for every star, it's helpful (and faster) to connect the dots between existing models in a process called interpolation. I developed Kiauhoku to be a user-friendly Python tool to interpolate new models from the grids that are built into it. I'm always looking to add new model grids, so get in touch if you'd like to contribute!
(Machine) Learning about Stellar Rotation
Stars rotate, and that rotation powers magnetism and atmospheric activity. We observe stars rotating by studying their light curves, which illustrate their brightness over time as cool, dark surface spots (think sunspots) rotate into and out of view. There are many ways to measure the spin rates from light curves, but I'm developing Artificial Intelligence tools to fill in the gaps left by other methods.
