Teaching

Grad school presented the opportunity to work as an Assitant in Instruction on courses for both undergraduate and graduate levels. My teaching style is personal and attentive, focusing on availability to students, due diligence, and connecting abstract mathematical concepts to practical examples and interesting applications within science and engineering. In 2020, I received Princeton's teaching award given annually by the Graduate School to a small number of teaching assistants across the university.

MAE 305 - Mathematics in Engineering I (Spring 2020 & Spring 2021)
Sophomore-level course for BSE students covering the theory and application of ordinary and partial differential equations. This course cumulatively builds up a toolkit of solution methods for ODEs, including separation of variables, Laplace transforms, and series solutions. These skills are ultimately applied in unison towards developing analytical solutions of basic PDEs. In order to build intuition, our course also included utilization of computational software tools, e.g., Wolfram Mathematica. My responsibilities included weekly review and problem-solving lectures, office hours, online forum moderation, and grading.

CBE 517 - Soft Matter Mechanics: Fundamentals & Applications (Fall 2022)
Graduate-level course surveying the mathematical treatment of a variety of soft matter systems, drawing on fields such as elasticity and interfacial fluid mechanics. Lectures covered a diverse array of topics, including elastica theory, interfacial instabilities, bifurcation theory, and the state of the art in soft matter research. Problem sets helped students to develop the solutions of canonical systems studied in class and extensively leveraged technical computing software, while the final projects allowed students to explore a soft matter topic of their choice. As an AI I held office hours, graded assignments, helped to develop the class syllabus, and provided guest lectures.