Teaching
As the Professor:
In Spring 2026, I’m teaching Python with Applications I at UCLA as the professor. I’m excited for this opportunity and I look forward to working with the students in my first ever class!
As a TA:
I’ve held teaching assistant positions (or equivalent) more or less continuously since 2021, between both the Australian National University and UCLA. I take joy in teaching, and I like to establish a connection with my students whenever possible. I consider it a great privilege to be part of my students’ university experience, and I take this responsibility seriously.
At the end of each academic term, I encourage my students to say hi if they see me on campus, and I usually joke that I owe them $5 if I don’t remember their name. Chances are that if you had me as a TA, I remember you and care how you’re doing, so feel free to reach out at any time for any reason. Hearing from or seeing my former students always makes my day.
Below is a summary of all the classes I’ve TA’d for and their content.
UCLA
Python with Applications I
In-depth introduction to the Python programming language for students who have already taken a beginning programming course in a strongly typed, compiled language (C++, C, or Fortran). Core Python language constructs, applications, text processing, data visualization, interaction with spreadsheets and SQL databases, and creation of graphical user interfaces.
Winter 2026
Introduction to Programming
Basic principles of programming, using C++; algorithmic, procedural problem solving; program design and development; basic data types, control structures and functions; functional arrays and pointers; introduction to classes for programmer-defined data types.
Winter 2024 - Fall 2025
Intermediate Programming
Abstract data types and their implementation using the C++ class mechanism; dynamic data structures, including linked lists, stacks, queues, trees, and hash tables; applications; object-oriented programming and software reuse; recursion; algorithms for sorting and searching.
Spring 2024
Integration and Infinite Series
Transcendental functions; methods and applications of integration; sequences and series
Fall 2023
Complex Analysis for Applications
Introduction to basic formulas and calculation procedures of complex analysis of one variable relevant to applications. Topics include Cauchy/Riemann equations, Cauchy integral formula, power series expansion, contour integrals, residue calculus.
Summer 2023
Linear Algebra
Techniques of proof, abstract vector spaces, linear transformations, and matrices; determinants; inner product spaces; eigenvector theory.
Spring 2023
Calculus of Several Variables
Introduction to differential calculus of several variables, vector field theory.
Winter 2023
Introduction to Discrete Structures
Discrete structures commonly used in computer science and mathematics, including sets and relations, permutations and combinations, graphs and trees, induction.
Fall 2022
ANU
Advanced Analysis 2: Lebesgue Integration and Hilbert Spaces
- Measure and Integration - Lebesgue outer measure, measurable sets and integration, Lebesgue integral and basic properties, convergence theorems, connection with Riemann integration, Fubini’s theorem, approximation theorems for measurable sets, Lusin’s theorem, Egorov’s theorem, Lp spaces, general measure theory, Radon-Nikodym theorem
- Hilbert Spaces - elementary properties such as Cauchy Schwartz inequality and polarization, nearest point, orthogonal complements, linear operators, Riesz duality, adjoint operator, basic properties or unitary, self adjoint and normal operators, review and discussion of these operators in the complex and real setting, applications to L2 spaces and integral operators, projection operators, orthonormal sets, Bessel’s inequality, Fourier expansion, Parseval’s equality, applications to Fourier series.
Semester 1, 2022
Advanced Analysis 1: Metric Spaces and Applications
Elementary set theory; metric spaces, sequences, uniform convergence, continuity, the contraction mapping principle; integral equations and differential equations, topological spaces.
Semester 1, 2022
Mathematics and Applications 2
- Calculus - Integration and techniques of integration, including multiple and iterated integrals. Sequences and series. Functions of several variables - visualisation, continuity, partial derivatives, and directional derivatives. Lagrange multipliers.
- Linear Algebra - theory and application of Euclidean vector spaces. Vector spaces: linear independence, bases and dimension; eigenvalues and eigenvectors; orthogonality and least squares.
Spring Session, 2021
Advanced Mathematics and Applications 2
- Calculus/Analysis - short introduction to metric spaces in the context of the calculus of functions of several variables, generalisation of real analysis theory to multivariable functions including limits and continuity, double integrals, Fubini’s theorem, integrability of continuous functions, partial derivatives, gradients and directional derivatives, differentiation of multivariable functions, extreme values, vector functions, curves and parametrisations, infinite series, convergence tests, power series, Taylor series.
- Linear Algebra - subspaces, span, linear independence, bases and dimension, linear maps, duality, eigenvalues and eigenvectors, inner product spaces, Gram-Schmidt orthogonalisation, operators on inner product spaces, the spectral theorem in finite dimensions, singular value decomposition.
Semester 2, 2021
Advanced Mathematics and Applications 1
- Calculus/Analysis - suprema and infima of sets of real numbers, completeness, Riemann-Darboux definition of integration, introductory formal logic, axioms for the real numbers, sequences, convergence, limits, continuity, related real analysis theorems including the monotone convergence theorem for sequences of real numbers and the Bolzano-Weierstrass theorem, existence of extrema, differentiation, applications of derivatives, proof of the fundamental theorem of calculus, Taylor polynomials, l’Hospital’s rules, inverse functions.
- Linear Algebra - solving linear equations, matrix equations, linear independence, matrix transformations, matrix operations, matrix inverses, abstract vector spaces, subspaces, dimension and rank, determinants, Cramer’s rule, complex numbers.
Semester 1, 2021