Conduct applied research and develop scalable systems for dynamic context graphs, knowledge representation, graph machine learning, information extraction, retrieval, and LLM-based reasoning. Build methods for entity and relationship resolution, temporal reasoning, provenance, uncertainty, and agentic workflows. Design evaluation benchmarks for graph quality and reasoning reliability, prototype systems with engineering teams, and contribute through publications, patents, technical strategy, and mentorship.