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About Me

I offer structured problem-solving, analytical thinking, and attention to detail to AI-driven applications. Having completed both the AUT-accredited Data Science and AI Certification (Institute of Data) and IBM's AI and Generative AI Engineering Professional Certificates, I have hands-on experience in implementing AI solutions.

Key Strengths

  • Analytical & Critical Thinking: Strong problem-solving and decision-making skills
  • Fast Learner & Adaptable: Quick to learn complex concepts (both theoretical and practical)
  • Creative Mindset: Merging critical thinking with innovative approaches

I am seeking an entry-level or junior AI/GenAI opportunity to help solve real-world challenges and contribute to impactful projects.

AI & Machine Learning

Multi-Agent RAG Systems
MCP (Model Context Protocol)
LLM Implementation & Orchestration
RAG Systems (Retrieval-Augmented Generation)
OCR & Document Processing
Computer Vision
Predictive Modeling & NLP

Technology Stacks

Programming & Frameworks

Python Flutter Tkinter Streamlit PyTorch Keras LangChain LangGraph Hugging Face

Automation & Integration

n8n Supabase Mistral OCR FastMCP

Generative AI & Vision

Multi-Agent Systems Stable Diffusion ControlNet YOLO RAG

APIs & Platforms

OpenAI API Google Gemini API Google AI Studio Ollama API

Skills & Expertise

Machine Learning

  • Multi-Agent RAG Systems with n8n Orchestration
  • Deep Learning with PyTorch
  • Object Detection with YOLO & ByteTrack
  • Retrieval-Augmented Generation & Self-Correction (LangGraph)
  • OCR Processing with Mistral & Document Analysis
  • Generative Modeling (Stable Diffusion XL & ControlNet)
  • Vision-Language Modeling with LLaMA 3.x Vision

Data & Cloud

  • Data Processing with NumPy & Pandas
  • Vector Storage with ChromaDB & Supabase
  • Embedding Generation (mxbai-embed-large)
  • Document Storage & Local-first Deployments (Notion MCP)
  • Cloud Database Integration & Vector Search
  • Google Colab & Drive Integration

AI Tools & Frameworks

  • n8n Workflow Automation & Multi-Agent Orchestration
  • Python & FastAPI (FastMCP)
  • LangGraph & LangChain Agents
  • Ollama (Local LLMs) & OpenAI GPT-4o
  • Supabase Vector Database & Real-time APIs
  • Hugging Face Diffusers with PyTorch, Pillow & OpenCV
  • Ultralytics YOLOv9 API & ONNX export
  • Tkinter GUI & FFmpeg for video processing
  • ChromaDB PersistentClient & Tavily Search API
  • Coqui TTS & Server-Sent Events (SSE)

Featured Projects

n8n Multi-Agent RAG System
Multi-Agent RAG

n8n Building Code RAG

Sophisticated multi-agent Retrieval-Augmented Generation system for New Zealand Building Code built entirely in n8n. Features specialized agents, OCR processing, and intelligent query routing with Supabase vector storage.

n8n OpenAI GPT-4.1 Mistral OCR Supabase Multi-Agent Vector Search
Notion MCP Agent
AI Agent

Notion MCP Agent

Notion‑MCP‑Agent turns your Notion workspace into a live, AI‑driven knowledge hub — now with text‑to‑speech. A FastMCP server exposes a rich toolbox for manipulating Notion pages. Using LangChain Agentic Framework and GPT‑4o orchestrates conversations, read, write, summarise, build tables, manage metadata, and even generate MP3s of your notes.

Tkinter Notion API TTS API LangChain & LangGraph FastMCP
GenAI Image Generation
Generative AI

GenAI Image Generation

Interactive Sketch to Image Tool using Stable Diffusion XL with ControlNet integration for precise image generation control.

Diffusers Stable Diffusion ControlNet PyTorch Tkinter
Vision Model RAG
ViT & RAG

Vision Model RAG

Vision Model RAG is a personal project designed to simplify information retrieval from the New Zealand Building Code documentation. Leveraging open-source technologies, it efficiently extracts, indexes, and retrieves textual and visual data from PDF documents.

Python LangChain & LangGraph Ollama ChromaDB Streamlit Unstructured io API
LLM RAG System
Advanced RAG

LLM RAG System

Self-Correcting Retrieval-Augmented Generation with autonomous decision-making for enhanced AI accuracy and reliability.

LangChain & LangGraph ChromaDB Ollama
Computer Vision Safety
Computer Vision

Computer Vision Safety

Object Detection for Safety Compliance on Construction Sites using YOLOv9 for real-time monitoring and hazard prevention.

Pandas & Numpy Matplotlib & Seaborn OpenCV PyTorch Real-time
CodeVision Flutter App
App Development

CodeVision Flutter App

Coming Soon: Web application for real-time code analysis, collaboration, and AI-powered development assistance.

Flutter Dart AI Assistant Web App LangChain & LangGraph Geminai API
YouTube Analytics
Data Science & Analytics

YouTube Analytics

Comprehensive statistical analysis of YouTube data science and AI content trends using API data collection, preprocessing, EDA, and hypothesis testing to identify temporal patterns and engagement changes.

Python YouTube API Pandas Statistical Analysis ANOVA Data Visualization
NASA Outgassing Analysis
Data Science & ML

NASA Outgassing Analysis

Machine learning application for NASA outgassing materials analysis. Develops predictive models using TML, CVCM, and WVR metrics for space-grade material evaluation and quality control.

Python Scikit-learn Regression Models Classification Feature Engineering Space Technology
AI Content Detection
Data Science & ML

AI Content Detection

Advanced NLP system for distinguishing human-written versus AI-generated news content using sophisticated text analysis, stylometric features, and machine learning models.

NLP NLTK spaCy Text Classification Deep Learning Feature Engineering
Wind Energy Prediction
Data Science & ML

Wind Energy Prediction

Machine learning system for predicting wind turbine power output using environmental data, weather patterns, and advanced regression models for renewable energy optimization.

Python Time Series XGBoost Neural Networks Energy Systems Regression Models

Let's Work Together

I'm always interested in discussing new opportunities, innovative projects, and collaborations in AI and technology. Let's connect and explore how we can create something amazing together.

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