Hi, I'm Freya, a dual-degree graduate student in Electrical Engineering & Computer Science (EECS) and City Planning (DUSP) at MIT. My work sits at the intersection of artificial intelligence, machine learning, and urban systems, with a focus on applying computational methods to real-world challenges in infrastructure, mobility, and environmental resilience.
At the City Form Lab, I lead spatial modeling projects that apply graph-based network analysis and geospatial indexing techniques to estimate pedestrian activity across Maine. I also contribute to a research using vision-language models to detect and analyze social behavior from large-scale street view imagery datasets. My technical work includes building scalable data pipelines and applying spatial indexing and trajectory modeling to extract insights from multi-source urban data.
Previously, I worked as a Machine Learning Engineer Intern at Symmons Evolution, where I designed predictive ML systems and LLM-powered diagnostic tools for real-time building energy management. My work focused on developing generative AI solutions that integrated structured sensor data, enhancing LLM reliability through prompt engineering.
With a strong background in computer vision, spatial analytics, and systems modeling, I'm passionate about advancing AI-driven approaches that bridge machine learning and LLMs with real-world challenges to design more intelligent, resilient, and inclusive systems.
