Coursework
Here’s a list of university-level courses I’ve taken at the University of Waterloo, along with some I’ve self-studied or audited. Auditing means I followed along independently—using course materials, attending or watching lectures, and doing assignments—without formal grades. I’m planning to add notes for some courses when I get the chance, so stay tuned!
Education
- BMath in Computer Science, University of Waterloo, expected May 2026
Coursework by Area
Computer Science
- CS 466: Algorithm Design and Analysis
- CS 480: Introduction to Machine Learning
- CS 485: Machine Learning Theory
- CS 761: Randomized Algorithms
- CS 798: Advanced Topics in Machine Learning Theory
- ECE 457C: Reinforcement Learning
Statistics
- STAT 433: Stochastic Processes II
- STAT 450: Estimation and Hypothesis Testing
- STAT 901: Probability Theory
- STAT 902: Stochastic Calculus
- STAT 929: Time Series
- STAT 946: Stochastic Differential Equations
- STAT 946: Mathematics of Deep Learning
Pure Mathematics
- PMATH 450: Lebesgue Integration and Fourier Analysis
- PMATH 451: Measure Theory
- PMATH 453: Functional Analysis
- PMATH 950: Analytic Methods in Convex Geometry
- PMATH 990: Introduction to Random Matrix Theory
Combinatorics and Optimization
- CO 430: Algebraic Combinatorics
- CO 442: Graph Theory
- CO 466: Continuous Optimization
- CO 739: Analytic Combinatorics
Course Projects
Here are some write-ups and presentations from my coursework projects:
- PMATH 950: Blaschke’s Characterization of Ellipsoids
Report - PMATH 940: An Elementary Proof of Hilbert-Waring Theorem (with Gian Sanjaya)
Presentation - CO 739: Positivity Problems for Low-Order Linear Recurrence Sequences
Presentation
Coming Soon
I’m working on adding notes and insights from reading groups, seminars, and self-study. Right now, I’m in Prof. Jeffrey Negrea’s reading group on online learning and a reading course with Prof. Greg Rice on time series analysis. More to come, so stay tuned!