Architect | Stateful Orchestration & Agentic Governance
Production-ready software spanning autonomous agent orchestration, quantitative finance, and deep learning infrastructure.
| Repository | Project Focus | Primary Stack |
|---|---|---|
| agenticAI | Stateful Orchestration — LangGraph-based agents with persistent SQLite memory and MCP tool integration. | Python, LangGraph, MCP |
| UdacityAITrading | Quantitative Finance — Signal processing, risk modeling, and alpha factor generation for trading. | Python, Pandas, NumPy |
| RAGs | Knowledge Retrieval — Advanced RAG implementations including Self-RAG and vector persistence. | LangChain, ChromaDB |
| Dockers | AI Infrastructure — Containerized environments for deploying scalable machine learning services. | Docker, Bash |
| DatascienceProjects | ML Foundations — Modular library covering NLP, Computer Vision, and Advanced Neural Networks. | TensorFlow, PyTorch, CV2 |
Detailed breakdown of research and development assets within the DatascienceProjects ecosystem:
- NLP & LLM: Transformer-based text classification and sentiment analysis.
- Computer Vision: Object detection and image segmentation modules.
- Deep Learning: Multi-layer perceptrons and sequence models.
- Machine Learning: Supervised/unsupervised pipelines and feature engineering.
- Fundamental Analysis: Statistical EDA and hypothesis testing.
- Agentic Frameworks: LangGraph, Multi-Agent State Machines, Breakpoints/HITL.
- Protocols: Model Context Protocol (MCP) for tool decoupling.
- Data Science: ML/ Advanced ML/ Deep Learning/ Computer Vision/ NLP/ Time-series forecasting, Financial ML, Alpha signals.
- DevOps: Dockerization, CI/CD for AI, Asynchronous services.
10+ Repositories · 15k+ Lines of Code · 8 Core AI Domains · 12 Private R&D Projects