Hi, I'm Antonio Zaitoun
I'm passionate about transforming data into meaningful insights and building robust systems that power intelligent applications. My work focuses on Ontology Learning & Evaluation, Large Language Models (LLMs), Natural Language Processing (NLP), and Scaleable Cloud Architectures.
Research Interests
My research focuses on developing domain-agnostic methods for ontology learning and evaluation, with applications in healthcare and other fields. I am particularly interested in exploring how large language models (LLMs) and natural language processing (NLP) can enhance knowledge representation, automate ontology evaluation, and address challenges in linked data systems.
Some of my recent contributions include:
- "Generating Ontology-Learning Training-Data through Verbalization"
- "OntoEval: An Automated Ontology Evaluation System"
- "Can Large Language Models Augment a Biomedical Ontology with Missing Concepts and Relations?"
You can explore my work on Google Scholar.
Pinned Projects
Open-Source Work
infragate/capa
One capabilities.yaml wires skills, tools, rules, sub-agents, MCP servers, and plugins into Cursor, Claude Code, Codex, Windsurf, GitHub Copilot, and 30+ other AI coding agents.
agentic-ontology-development-kit
AI-assisted ontology development: scope, knowledge exploration, and formalization with OWL and reasoning tools.
ontology-verbalizer
OWL Ontology Verbalizer — enables the conversion of OWL ontologies and RDF graphs into human-readable text.
owl-mcp
MCP server for modifying OWL files, written in Rust.
AZDialogViewController
A highly customizable alert dialog controller that mimics Snapchat's alert dialog, written in Swift.
AZTabBarController
A custom tab bar controller for iOS written in Swift 4.2.
