Sophia Kazinnik

Research Team
AI agents can become a new kind of economic laboratory: we can endow them with information, incentives, and constraints, then watch how beliefs, coordination, and panics emerge. At the Lab, I build agent-based systems with LLMs, not just to forecast outcomes, but to run controlled what-if worlds that help us understand mechanisms and design better interventions.
Areas of Research
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kazinnik@stanford.edu
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Sophia Kazinnik is a Research Scientist at Stanford’s Digital Economy Lab (HAI), where she builds generative AI systems to explore how language and behavior shape economic outcomes. Her work turns economic questions into computable experiments, using LLM-powered agents and multi-agent simulations to study financial fragility, policy communication, and market expectations. In some of her recent projects, she has modeled bank runs, simulated FOMC deliberations, and evaluated how today’s AI interprets central bank language.

Before joining Stanford, Sophia spent seven years as a Financial Economist & Quant at the Federal Reserve, where she reviewed stress-test models and developed natural language tools for bank supervision. Across her research on AI-augmented surveys, simulated professional forecasters, and the analysis of verbal and nonverbal cues in central bank communication, her goal is to make AI a lab for studying economic behavior, and a tool for designing better policy.