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Achievement: Pull Shark

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Achievement: Pull Shark

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sha-huang/README.md

👋 Hello! This is Sha.

Please find a self-introduction at my personal website: sha-huang.github.io

I work in the energy commodities trading industry, with a focus on Liquefied Natural Gas (LNG). More information on my LinkedIn profile.

Driven by a passion for computer science, I studied:

Area Details
Theory foundations
  • Data structures and algorithms
  • Computer architecture
  • Operating systems
  • Programming languages theory
  • Statistical machine learning
  • Deep learning
Statically typed languages
  • C
  • Java
Dynamically typed languages
  • Python (and libraries)
  • JavaScript
Database
  • PostgreSQL
Systems and tools
  • Linux
  • Git
  • $\LaTeX$

Currently learning:

  • Rust
  • Reinforcement learning
  • Agentic AI (my notes of the UC Berkeley CS294/194-196 guest lecture series on GitHub)

Pinned Loading

  1. ucb-agentic-ai ucb-agentic-ai Public

    Study notes of the Agentic AI guest lecture series at the University of California, Berkeley.

  2. agent-code agent-code Public

    A minimalist SWE agent CLI adapted for the Google Gemini generateContent API

    Python

  3. sha-huang.github.io sha-huang.github.io Public

    Sha Huang's personal website hosted on GitHub.

    HTML

  4. parameter-golf parameter-golf Public

    Forked from openai/parameter-golf

    Train the smallest LM you can that fits in 16MB. Best model wins!

    Python

  5. xv6-riscv-book xv6-riscv-book Public

    Forked from mit-pdos/xv6-riscv-book

    Text describing xv6 on RISC-V

    TeX

  6. concurrent_and_parallel_programming concurrent_and_parallel_programming Public

    Forked from PacktPublishing/Concurrent-and-Parallel-Programming-in-Python

    Concurrent and parallel programming practices

    Python