Academics

I study Electrical Engineering & Computer Sciences, Economics, and Data Science at UC Berkeley. This page highlights selected class projects and a concise record of coursework.


Projects by Course

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  • RISC-V CPU (Logisim) Hardware / Architecture

    Built a fully functional RISC-V CPU supporting all 7 instruction types; verified with custom test benches.

    Demo · Repo
  • Handwritten Digit Classifier (RISC-V) ML Systems

    Feedforward NN with matrix multiply, ReLU, argmax; optimized for constrained RISC-V environment.

  • Perspectives & The Dolly Zoom Introductory

    Exploring how focal length, perspective, and camera position shape images.

  • Filters & Frequencies in Images Image Processing

    Explored image processing by treating images as functions: implemented filtering, sharpening, hybrid images, and frequency-based blending.

  • Pac-Man AI Econometrics / Markets

    Hidden Markov regimes on VX term-structure; dynamic risk controls; out-of-sample stress tests.

  • Policy & Markets Notes Applied Micro

    Short analyses linking regulatory shifts to liquidity, spreads, and sector-level dynamics.


Full Coursework

EECS

  • EECS 16A/B: Designing Information Systems
  • CS 61A: Intro to Computer Programs
  • CS 61B: Data Structures & Algorithms
  • CS 61C: Great Ideas in Computer Architecture
  • CS 70: Discrete Mathematics & Probability
  • EECS 120: Signals & Systems
  • EECS 126: Probability and Random Processes
  • EECS 127: Optimization Models in Engineering

Machine Learning

  • STAT 20: Intro to Statistics
  • DATA C100: Principles & Techniques of Data Science
  • CS 180: Intro to Computer Vision
  • CS 188: Intro to Artificial Intelligence
  • CS 189: Intro to Machine Learning

Economics

  • ECON 1: Intro to Micro/Macro
  • ECON 100A/B: Micro/Macro Theory
  • ECON C110: Game Theory
  • ECON 136: Intro to Financial Economics
  • ECON 138: Intro to Behavioral Economics
  • ECON 140: Econometrics