New York, United States
I am a Master in Urban Planning candidate at the Harvard Graduate School of Design, concentrating in urban analytics. With a background in Economics and Mathematical Probability from Columbia University, my work sits at the intersection of data science, spatial planning, and systemic impact. My research applies econometrics, network science, and machine learning methods to advance innovation and resilience across real estate, infrastructure planning, and climate systems. Increasingly, my focus centers on AI governance and safety, specifically GeoAI alignment, ensuring that spatial algorithms and autonomous systems deployed in our physical world are safe, equitable, and aligned with human values. I am deeply motivated to apply this cross-disciplinary toolkit toward three global imperatives: ā” Accelerating the global energy transition š² Advancing global Vision Zero traffic safety initiatives š¼ Fostering equitable economic growth (expanding high-quality jobs, resilient industries, healthy workplaces, improved education, and poverty eradication) Recently, I worked as a Product Development Intern at Block Party, where I leverage core competencies in product management and PostgreSQL to build and demo civic-technology tools (geotagging messy datasets). My professional trajectory spans innovation strategy at Mormedi and policy research at the Columbia Climate School. I also write about the evolving intersection of cities, safety, and artificial intelligence at Load Bearing on Substack. Always open to connecting with fellow researchers, planners, and builders working on the future of cities and safe spatial AI. View My Work: [See featured section or email to hear me talk about my most recent work to you!] Email: [email protected] Newsletter: Substack: The Algorithmic Commons