My name is Tyler Zhu, and I'm a 2nd-year EECS undergraduate at the University of California, Berkeley.
Broadly, my main interests are mathematics and computer science, but I'm currently focused on machine learning, especially in model robustness and efficiency.
Aside from academics, I find human behavior (especially cognition) and social dynamics fascinating, and play guitar and basketball (big Giants and Warriors fan).
I also enjoy dancing, and am a huge foodie and coffee savant. If you're equally interested in any of the above, let's chat!

Here's an abridged summary of the classes I have taken. Some of them have links to
additional resources that I've created. The notes are written in LaTeX and
live during lecture, so they may contain many errors. I try my best to correct them after the fact. My setup is
inspired by that of Evan Chen's.

- CS 161: Computer Security
- CS 271: Randomness and Computation
- Math 191: Nonlinear Algebra

- CS 61C: Great Ideas of Computer Architecture
- CS 189: Introduction to Machine Learning
- Math H104: Honors Introduction to Real Analysis

- CS 61B: Data Structures
- CS 170: Efficient Algorithms and Intractable Problems
- EECS 126: Probability and Random Processes
- Math 255: Algebraic Curves

- CS 47A: Structure and Interpretation of Computer Programs
- CS 70: Discrete Mathematics and Probability Theory
- CS 188: Introduction to Artificial Intelligence
- EE 16A: Designing Information Devices and Systems I