AI Engineer & Computational Scientist focused on LLMs, RAG, knowledge graphs, FAIR research data infrastructure, semantic data systems, and computational modelling.
I have a PhD in Computer Science in computational modelling and simulation. My work connects scientific computing with practical AI engineering: building systems where research data, metadata, knowledge graphs, and LLM workflows become usable, reliable, and AI-ready.
- AI Engineering: LLMs, RAG, GraphRAG, agentic systems
- Knowledge Graphs: Neo4j, RDF, SPARQL, semantic data modelling
- FAIR Data: research data infrastructure, metadata, data integration
- Scientific Computing: computational modelling, simulation, biomolecular systems
- Research Software: Python, FastAPI, ETL pipelines, Docker, Kubernetes, JupyterHub
I am building and documenting projects around:
- GraphRAG over research and scientific data
- FAIR metadata workflows for AI-ready datasets
- Knowledge graph pipelines using Neo4j, RDF/SPARQL, and Python
- LLM-based assistants for domain-specific data exploration
- Cloud-native research data infrastructure
Python 路 FastAPI 路 Neo4j 路 RDF/SPARQL 路 PostgreSQL 路 Docker 路 Kubernetes 路 JupyterHub 路 LLMs 路 RAG 路 GraphRAG 路 FAIR Data 路 Knowledge Graphs 路 Computational Modelling
- Website: vinaygautam.com
- LinkedIn: linkedin.com/in/vinaygautam