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Science Olympiad is a science competition in which teams of 15 compete in 23 different events. I was a competitor in high school for 3 years and I'm now involved in running the Astronomy and Data Science events. I've supervised Astronomy at various tournaments across the nation, including UT Invitational, MIT Invitational, Princeton Invitational, and Nationals. More recently, I've written rules for a new Data Science trial event, which is now an official state event in Texas. I'll be running this event at the Texas state tournament.

In Astronomy, the goal is to develop students' understanding of astrophysical processes. The focus of the event varies on a yearly basis (e.g. supernovae, galaxies, exoplanets, etc.), but there are several common underlying themes (e.g. stellar evolution and classification, basic observational astronomy, and basic celestial mechanics).

Data Science is a computer science event which aims to expose students to the intersection of programming, statistics, and machine learning. The role of computation in traditional science research (and as a field on its own) can't be understated, and I think it's important for aspiring scientists to be exposed to modern ideas in computer science. Plus, it's hella cool. You can find the rules here.

You can find posts relating to Science Olympiad here. Or you can read here about my background and why I'm still involved.

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