Teaching Table of Contents

I have additional teaching experience through outreach.

ASTR 300A: Dynamics in Astrophysics

In the Fall of 2018 at the University of Arizona, I was the only teaching assistant for AST 300A: Dynamics in Astrophysics. The course is the second astrophysics course taken by astro/physics majors and is taught by my research advisor Kaitlin Kratter. My responsibilities consisted of attending every class, holding four hours of office hours each week, and grading homework and exams. I also taught one class in which students completed a computational activity designed by my academic sister Rachel Smullen.

The course covers three main topics: planetary orbital dynamics, galactic dynamics, and hydrodynamics. Check out some figures from the homework solutions below. I made all but one of these.

Jupiter, but as a ring

A problem from the class: Derive the gravitational potential of Jupiter at the Earth if it were a ring at distance R from the Sun.

Kicking satellites

What do we have to do to the satellite to change its orbit from black to red?

Sending a satellite to the Moon

The next part of the problem: Get the satellite to the Moon!

Roche Lobe overflow

Something, something, Roche Lobe overflow...

CS 6780: Advanced Machine Learning

In the Spring of 2015 at Cornell, I was a teaching assistant for CS 6780: Advanced Machine Learning. The course is a graduate-level introduction to machine learning taught by Thorsten Joachims. My responsbilities consisted of grading homework assignments and an exam.

The graduate level course is nearly identical to the undergraduate version of the course, except that it is taught at a faster pace, covers additional material at the end, and has a more demanding final project. The TA staff consisted of two lead graduate student TAs who did machine learning research with Prof. Joachims, and about eight undergraduate TAs who had only taken the undergraduate course and were mainly on the staff to help with the large amount of grading.

The undergraduate version is available online with lecture slides and videos, but not assignments or exams.

A generic support vector machine. You will learn about this in a machine learning course.

Contact Info

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