I'm passionate about AI, machine learning, and data science. I thrive on learning and sharing new technologies.
Right now, I'm at Neo4j, where I get to work on cool projects with GenAI and graph databases. Whether it's developing coded examples, creating demo apps, writing blogs, supporting sales & solutions, or delivering technical presentations, I love sharing knowledge and helping others leverage these tools.
Off the clock, you'll find me tinkering with new projects, staying updated on the latest AI trends, or trying to stay young by lifting progressively heavier things (powerlifting). Feel free to check out my projects below or connect with me if you want to chat!
- Graph-ND (Knowledge in Graphs, not Documents): code - a new Python project for building end-to-end GraphRAG systems with a simple, intuitive API.
- Boosting Q&A accuracy with graph DBs & graph neural networks (GNNs) + LLM fine-tuning with G-Retriever:
- Agentic AI for supply chain & bill of materials: code - Supplier substitution search, country & trade dependency analytics for complex BOMs with mixed intel, parts search and comparisons, etc. End-to-end example with deployment on GCP
- Agentic AI for customer & retail analytics dev guide & code - leverages mixed data with GraphRAG. End-to-end example from data loading, to designing retrieval tools, and building an agent
- Improving customer experiences with AI & GraphRAG applications: dev guide & code
- Hands-on AI & graph workshops, run globally for in-person events with prospects & customers
- Demo application for GraphRAG patterns: code & webinar recording
- Graph Data Science for fraud detection: blog & code
- Graph Data Science for recommendation systems: blog & code
- Graph machine learning overview (blog)
- A collection of technical resources for Graph Neural Networks (GNNs) with Neo4j Graph Data Science including graph feature engineering for improving model performance in inductive and transductive settings.