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huangbogeng/README.md

Hi, I'm Alex Huang 👋

Quant Research × Rust Systems × High-Performance Data Infrastructure

I build tools for alpha research, backtesting, model inference, and developer productivity — with a strong preference for Rust, Polars, Python, and clean system boundaries.

GitHub followers Profile views Rust Python Polars


What I focus on

I care about building research infrastructure that is fast, explicit, testable, and close to production.

  • Performance engineering: Rust-native libraries, low-latency data paths, CPU inference, and async/non-blocking designs.
  • 📈 Quant research tooling: factor mining, backtesting engines, trading calendars, data access layers, and analysis workflows.
  • 🧠 ML infrastructure: lightweight model runtimes and predictable inference behavior.
  • 🛠️ Developer tools: small utilities that remove friction from daily engineering workflows.

Featured projects

High-performance non-blocking logging for Rust.

Built around a Disruptor-style ring buffer, batch flushing, preallocated records, thread-safe counters, and graceful shutdown semantics.

A Rust-powered backtesting plugin for Polars.

Designed for strategy evaluation with efficient order matching, long/short position tracking, limit price handling, and a Python API that integrates with Polars DataFrames.

A high-performance alpha mining framework.

Provides an integrated research workflow for factor researchers: trading calendars, data access, factor construction, Rack-based data integration, and Polens factor analysis.

A focused Rust inference runtime for official XGBoost model.json files.

Loads supported upstream models, runs CPU prediction, validates model boundaries, and fails explicitly when a model is outside the supported scope.

Developer tool highlight

A browser-based management UI for Claude Code provider configurations.

Replaces manual JSON editing with one-click provider switching, built-in provider presets, API key / OAuth flows, local proxy support, and live synchronization with Claude Code configuration.


Tech stack

Core interests: Rust, Python, Polars, PyO3, Maturin, Axum, React, TypeScript, quantitative research systems, backtesting engines, factor analysis, model inference.


Project map

Area Project What it demonstrates
Logging infrastructure nanolog-rs Non-blocking Rust logging, ring buffers, batching, graceful shutdown
Backtesting engine polars_bt_extension Rust + Polars plugin design, order matching, P&L calculation
Alpha research platform alpha-lab Factor research workflow, data access, trading calendars, analysis tools
ML inference runtime xgboost-rs Rust-native XGBoost model loading and CPU prediction
Developer productivity cc-switch-ui Rust backend + React frontend + local config automation

GitHub stats


Working style

Make the research loop faster. Make the system boundary clearer. Make correctness visible before performance becomes dangerous.

I like projects that sit at the intersection of research productivity and systems engineering: small enough to understand, fast enough to matter, and explicit enough to trust.


Thanks for visiting.

If you are interested in quant infrastructure, Rust performance engineering, or research tooling, feel free to explore the repositories above.

Pinned Loading

  1. nanolog-rs nanolog-rs Public

    Rust 高性能异步日志库

    Rust

  2. polars_bt_extension polars_bt_extension Public

    A high-performance backtesting engine plugin for Polars

    Rust

  3. cc-switch-ui cc-switch-ui Public

    Using CC Switch on systems without a desktop environment, like Linux servers or cloud servers.

    Rust 3

  4. polars_ds_extension polars_ds_extension Public

    Forked from abstractqqq/polars_ds_extension

    Polars extension for general data science use cases

    Rust

  5. xgboost-rs xgboost-rs Public

    Rewrite xgboost using Rust

    Rust

  6. GDUF-QUANTLAB/alpha-lab GDUF-QUANTLAB/alpha-lab Public

    A high-performance alpha mining framework

    Python 9