My education

I’m in the class of 2017-2021 at Stanford. I’m a Mathematical and Computational Science Major, with a view to doing a Computer Science PhD or Master’s. I’m also working towards a History Minor.

GPA: 4.13

Right Now:

  • CS 330: Deep multi-task and meta-learning

  • CS 224W: Machine Learning with Graphs

  • CS 154: Automata and complexity theory

  • Math 120: Groups and Rings (Honors)

  • CS research in the IRIS lab

CS Classes:

  • 43: Functional Programming Abstractions in Clojure (S)

  • “The CS Core”—103, 106B, 107, 110, 161: (3 A+’s, 2 A’s. I got the top grade in a couple of ‘em.)

  • 166: Data Structures (A+)

  • 221: AI: Principles and Techniques (A)

  • 228: Probabilistic Graphical Models (A)

  • 229: Machine Learning (A+)

  • 261: Optimisation and Algorithmic Paradigms (A)

Math Classes:

  • 51: Linear Algebra and Multivariable Calculus (A+)

  • 52: Multivariable Integral Calculus (A+)

  • 53: Differential Equations (A)

  • 151: Theory of Probability (A+ — this also substitutes 109 in the CS core.)

  • 159: Discrete Probabilistic Methods (A+)

  • 171: Real Analysis (Honors) (A)

The data structure we made for CS 166: it’s called a “Relaxed Margin-Maximising Hyperplane” tree. It deals well with low intrinsic dimensionality, and outperformed basically every other K-D Tree variant for nearest neighbour search.

The data structure we made for CS 166: it’s called a “Relaxed Margin-Maximising Hyperplane” tree. It deals well with low intrinsic dimensionality, and outperformed basically every other K-D Tree variant for nearest neighbour search.