Zhijing Jin

Max Planck Institute for Intelligent Systems, Tübingen 🇩🇪 and ETH Zurich 🇨🇭
Causality for Natural Language Processing

Zhijing’s research pioneered a causal foundation for modern natural language processing and large language models. Her dissertation introduced rigorous causal frameworks that reveal how language models reason, generalize, and interact, enabling more robust, interpretable, and socially responsible AI systems. She has advanced understanding across causal inference, AI safety, and multi-agent LLMs, offering new tools to diagnose and mitigate bias, evaluate moral and social reasoning, and analyze emergent cooperation in LLM societies. Her work charted a path toward trustworthy AI that can reason about cause and effect, align with human values, and support equitable impact across global communities.