I received an M.A. in Mathematics from UNL in 2019 and a B.A. from Colorado College in 2016.

I was previously the Math Department's representative to the UNL Graduate Student Association (GSA). Currently, I serve as Chair of the GSA Communications Committee.

I have also participated in speaking and support roles for the Great Plains Alliance, a program which sends UNL grad students to give talks at nearby institutions.

- The Simple Random Walk on the Hypercube (UNL Discrete Seminar Fall 2021)
- The Heat Equation on the Discrete Cirlce (UNL STAARS Seminar, Fall 2021)
- Discrete Harmonic Functions, the Dirichlet Problem, Random Walks, Gambling, etc. (UNL STAARS Seminar, Spring 2021)
- Expander Codes (UNL Discrete Seminar, Fall 2020)
- The Saddle-point Method for Asymptotic Enumeration (UNL STAARS Seminar, Fall 2020)
- The Spectral Theory of Finite Markov Chains (UNL STAARS Seminar, Spring 2020)
- The Differential Equations Method, 1 & 2 (UNL STAARS Seminar, Spring 2020)
- Encoding arguments (UNL Discrete Seminar, Fall 2019)
- An introduction to determinantal point processes (UNL STAARS Seminar, Fall 2019)
- Card shuffling and Markov chains (UNL Discrete Seminar, Spring 2019)
- The mathematics of gerrymandering (Great Plains Alliance talk, Drake University, Fall 2018)
- Sampling and graph problems in redistricting (UNL Discrete Seminar, Fall 2018)

- Math 221 - Differential Equations (Instructor Spring 2021 & Spring 2022)
- Math 300 - Mathematics Matters (Instructor Fall 2021)
- MATH 106 - Calculus I (Instructor, Fall 2020)
- MATH 435 - Math in the City (TA, Fall 2019 & Spring 2020)
- MATH 101 - College Algebra (Instructor, Fall 2018 & Spring 2019)
- MATH 107 - Calculus II (TA, Fall 2017 & Spring 2018)

For the Fall 2019 and Spring 2020 semesters, I was the TA for MATH 435 - Math in the City, a capstone course for math majors in which students complete group research projects in a particular (usually applied) topic. The topic for that year was gerrymandering. Both semesters, I mentored groups that wrote their own Markov Chain Monte Carlo algorithms in Python for sampling districting plans on a generalized U.S. state. You can read more about our course from Fall 2019 in this Lincoln Journal Star piece.

__Homology and Data__(Undergraduate thesis)

A primer on persistent homology.