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Building trading, risk, compliance, and AI systems
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Building trading, risk, compliance, and AI systems
  • Financial Engineering
  • 03:40 (UTC +01:00)

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JordiCorbilla/README.md

Hi there 👋

Jordi Corbilla — Senior Full-Stack and Quantitative Engineer

I’m a Senior Full-Stack & Quantitative Engineer building trading, compliance, risk, and AI systems.

With over two decades of experience designing and delivering end-to-end software, I specialize in systems that need to be fast, reliable, scalable, and production-ready. My focus is the architecture and implementation of mission-critical platforms for complex, high-volume financial environments.

My work sits at the intersection of Python, C#/.NET, cloud-native engineering, portfolio analytics, and agentic tooling. I’m particularly interested in systems where strong engineering discipline, quantitative thinking, and practical automation come together to solve difficult real-world problems.

My academic background includes a Master’s in Computer Engineering and a Bachelor’s in Computer Engineering, both from the Open University of Catalonia, as well as a Bachelor’s in Industrial Electronics Engineering from the University of Girona.

I have also completed advanced specializations in IBM RAG and Agentic AI, IBM Data Science, Investment Management with Python and Machine Learning, Financial Engineering and Risk Management, and Machine Learning.

I use this space to share projects across quantitative finance, AI, developer tooling, and applied machine learning. If you only look at one project, start with RiskOptima.

Flagship Projects

The projects that best represent how I combine quantitative thinking with production engineering.

RiskOptima table.lib

Stock Prediction with Deep Neural Learning LangGraph Cookbook

Recent Work

A rolling selection of newer work across quantitative platforms, language models, trading infrastructure, and production engineering.

RiskOptima Platform FrankenGPT: LLM from Scratch

Quantitative Developer Reference Library FIX Protocol Knowledge Base

React Forge Kit .NET Low-Latency Playbook

More Quant Finance, AI & Engineering

Efficient Frontier Monte Carlo Portfolio Optimization Index Volatility Divergence Signals

Portfolio Optimization Probability Analysis Quantitative Finance

RAG PDF Chatbot AI Tutor

Explore all repositories →

Pinned Loading

  1. stock-prediction-deep-neural-learning stock-prediction-deep-neural-learning Public

    Predicting stock prices using a TensorFlow LSTM (long short-term memory) neural network for times series forecasting

    Jupyter Notebook 685 126

  2. ocular-disease-intelligent-recognition-deep-learning ocular-disease-intelligent-recognition-deep-learning Public

    ODIR-2019: Ocular Disease Intelligent Recognition is a project leveraging state-of-the-art deep learning architectures to analyze and classify ocular diseases based on medical imaging data. This re…

    Jupyter Notebook 74 27

  3. table.lib table.lib Public

    Simple c# (.NET 8/.NET 10) table library that renders any List<T> or Dictionary<TV, T> into a nicely formatted markdown, CSV, HTML, specflow or console table, allowing for extra formats. It also su…

    C# 24 3

  4. RiskOptima RiskOptima Public

    The RiskOptima toolkit is a comprehensive Python solution designed to assist investors in evaluating, managing, and optimizing the risk of their investment portfolios. This package implements advan…

    Jupyter Notebook 6

  5. thundax-delphi-physics-engine thundax-delphi-physics-engine Public

    🛴 "Thundax Delphi Physics Engine" is a Delphi-based 2D physics engine for simulations and visualizations. It employs Pascal and is ideal for learning and experimenting with 2D physics concepts.

    Pascal 79 20

  6. atom-table-monitor atom-table-monitor Public

    ⚛️ Monitoring tool for global atom table and RegisterWindowMessage identifiers

    Pascal 72 13