Machine Learning Research Intern

Pelagic AI

Jun. 2025 – Aug. 2025 | Mclean, VA

As a Machine Learning Research Intern at Pelagic AI, I focused on developing advanced AI infrastructure to support complex simulation environments for government applications.

Key Contributions

  • Implemented Model Context Protocol (MCP) server architecture enabling LLM-driven LangGraph agents to orchestrate complex simulations constrained to stringent government performance requirements

  • Developed a distributed simulation environment that processes satellite imagery geopolygons to generate realistic airport scenarios, integrating real-world OpenStreetMap data with graph-based spatial modeling using NetworkX

  • Built modular persistence layer with type-safe data for airport infrastructure and dynamic vehicle tracking, deployable with a robust Docker containerization structure

Technologies Used

Python • LangGraph • Model Context Protocol • NetworkX • OpenStreetMap • Docker • Satellite Imagery Processing • Graph-based Spatial Modeling