
Master Thesis Intern
Electronic Arts
- Researched and built an LLM-based agent system to predict CI build failures at scale, achieving a precision of 70% and recall of 84%.
- Designed and evaluated multiple architectures such as RAG and GraphRAG for automated CI failure prediction under data scarcity conditions.
- Integrated a Neo4j knowledge graph with an LLM agent, enabling structured reasoning over build history.
- Conducted rigorous ablation studies across configurations to isolate the contribution of each system component.



