Ibraheem Syed

Bachelor's

Computer Science

T-Mobile

Machine Learning Intern

• Benchmarked AI retrieval methods including RAG, fine-tuning, and graph reasoning for RF-domain Q&A • Achieved 95% of larger model performance with a smaller knowledge graph–augmented LLM, reducing compute and power • Architected multi-hop knowledge graph text retriever with Neo4j and ChromaDB, using custom traversal heuristics • Developed modular retrieval pipelines combining vector DBs and structured graphs for contextual LLM input