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@simonw
@unslothai

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@Nelumbium-Capital

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JunjieAraoXiong/README.md
Currently Exploring
  • Building distributed training pipelines for large-scale ML models
  • Developing low-latency market data processing systems
  • Implementing consensus algorithms for fault-tolerant systems
Looking For
  • Undergraduate research in ML systems or distributed computing
  • Summer 2026 internships in SWE, MLE, or Quant

Tech Stack that I am exploring✨

Python
Python
C
C
Java
Java
TypeScript
TypeScript
React
React
Node.js
Node.js
Flask
Flask
PyTorch
PyTorch
TensorFlow
TensorFlow
HuggingFace
HuggingFace
scikit-learn
sklearn
NumPy
NumPy
Pandas
Pandas
Spark
Spark
PostgreSQL
PostgreSQL
Neo4j
Neo4j
Linux
Linux
Docker
Docker
Git
Git
LangChain
LangChain
LlamaIndex
LlamaIndex

Pinned Loading

  1. Return-To-The-Tomb Return-To-The-Tomb Public

    A VR reconstruction of the Saqqara necropolis and Psamtek’s Late Period sarcophagus, built in Unity for HTC Vive and Meta Quest.

    ASP.NET 1

  2. cs61a-tutor cs61a-tutor Public

    Fine-tuning LLMs with RL to solve and explain CS61A problems

    Python

  3. Nelumbium-Capital/GraphMert Nelumbium-Capital/GraphMert Public

    End-to-end neurosymbolic pipeline for constructing high-quality financial knowledge graphs from unstructured data and integrating them into agent-based simulations for market and risk analysis.

    Python 1

  4. financial-risk-intelligence financial-risk-intelligence Public

    Comparing structured (Knowledge Graph) vs unstructured (RAG) approaches to financial risk intelligence in multi-agent crisis simulations

    Python 3