I’m an engineering student specializing in data science and machine learning engineering. I strive to build useful services for day‑to‑day needs, integrate state‑of‑the‑art AI models into complex workflows, and I’ve recently started building my own models. I've also had a surprising lot of fun transforming and funneling data for machine learning "challenges".

As I’m nearing the end of my studies, I’m looking for an internship by 2026! Here’s my LinkedIn (resume available there):
👉 https://www.linkedin.com/in/raphael-nguyen-162974225/

Here is an overview of some of my projects. You can of course browse the rest of my public repositories from here https://github.com/Ryustiel?tab=repositories

• Meep — Multi‑Interface Conversational Platform
  https://github.com/Ryustiel/MeepPublic
  Modular agent built on LangGraph with unified state across multiple chats, async MCP‑style tools, and HITL approvals; designed for scalable, multi‑channel conversations.
  Tech: LangGraph, LangChain, Discord.py, Streamlit, asyncio, Docker Compose, OpenAI, google-generativeai SDK.

• RAGraph — Relational Accessor Graph
  https://github.com/Ryustiel/Ragraph
  Dynamic, multi‑layer knowledge graph for RAG that retrieves context via weighted semantic “accessors” over PostgreSQL + pgvector—great for messy, LLM‑extracted knowledge bases.
  Tech: Python, SQLAlchemy, PostgreSQL/pgvector, Pydantic, OpenAI embeddings.

• Automated Email & Document Processing Pipeline (LLM Storage Service)
  https://github.com/Ryustiel/LLMStorageServicePublic
  Async, containerized pipeline that ingests emails, OCRs attachments, and summarizes content with GPT; pluggable content‑addressable storage (Local, S3, Google Drive).
  Tech: FastAPI, Docker Compose, LangChain, OpenAI, Mistral OCR, S3/GDrive, asyncio.

• Spark + PyTorch: Distributed LSTM for Time‑Series Forecasting
  https://github.com/Ryustiel/SparkTorchPublic
  End‑to‑end workflow using Spark for large‑scale preprocessing and PyTorch DDP via TorchDistributor for distributed LSTM training on time‑series data.
  Tech: Apache Spark, PyTorch (DDP), TorchDistributor, PyArrow, Docker.

• Gemini ImageChat
  https://github.com/Ryustiel/GoogleGenAI
  A Streamlit app to chat with Google’s Gemini image model: attach local images and receive generated images in the conversation; outputs are auto‑saved to project folders.
  Tech: Streamlit, google‑generativeai SDK, PIL, GCP service account.

• Aym — Conversational Graph Builder
  https://github.com/Ryustiel/SI28-Aym
  Turn LLM debates into a living knowledge graph with tool‑proposed node/edge edits and human confirmation, rendered live in an interactive 3D Plotly view; persisted as a single JSON graph.
  Tech: Streamlit, Plotly, LangChain, OpenAI, Pydantic, aiofiles.

If anything catches your eye or you’d like to collaborate, feel free to reach out on LinkedIn.⁣⁠⁣​‌‌‌​​‌​​‌‌​​‌​‌​‌‌‌​​‌‌​‌‌‌​​​​​‌​‌‌‌‌‌​​‌‌​​​​​​‌‌‌​​​​‌‌​​‌​‌​​‌‌​​​‌​​‌‌​‌​​​​‌‌​​‌‌​​‌‌​‌‌‌​‌‌​​‌‌​​​‌‌​​​‌​‌‌​​​‌​​‌‌​​​‌​​‌‌​​​‌​​‌‌​​​​‌​​‌‌​​‌​​‌‌​​​‌​​​‌‌​​​‌​​‌‌​​​​​​‌‌​​​​​​‌‌​‌‌​​​‌‌‌​​​​‌‌​​‌​‌​​‌‌​​​‌​​‌‌​‌‌​​‌‌​​​​‌​​‌‌​‌​​​​‌‌​​​​​‌‌​​​‌​​​‌‌​​​​​​‌‌​‌‌​​​‌‌‌​​​​​‌‌‌​​​​​‌‌​​​‌​​‌‌‌​​‌​‌‌​​‌​‌​​‌‌‌​​‌​‌‌​​‌​​​​‌‌‌​​​​​‌‌‌​​​​‌‌​​​‌‌​‌‌​​‌​‌​‌‌​​‌​‌​​‌‌​‌​‌​‌‌​​​​‌​​‌‌​‌​​​​‌‌‌​​‌​​‌‌​‌​​​​‌‌​​‌‌​​‌‌‌​​​​‌‌​​​‌​​​‌‌​​​‌