Summary
Zhijing Jin is an Assistant Professor at the University of Toronto and a CIFAR AI Chair with an interdisciplinary PhD in AI focused on NLP, causality, and computational social science, trained under Bernhard Schölkopf, Rada Mihalcea, and Mrinmaya Sachan. With eight years of research experience across Max Planck, ETH, MIT, Meta, and AWS, she develops methods that use natural language to reason about causal questions and inform policy for social good. Her work bridges rigorous causal inference and practical NLP applications—spanning policy analysis, knowledge-graph/text generation, and responsible AI—resulting in multiple high-impact publications and industry internships. Based in Germany, she combines academic leadership with hands-on research scientist roles at Max Planck and contributions to applied teams (e.g., Meta Responsible AI), reflecting a rare mix of theoretical depth and production-oriented experimentation. An intriguing throughline in her career is a persistent focus on real-world impact: from autism education and field volunteering to algorithmic tools aimed at effective altruism–guided policy interventions.
8 years of coding experience
3 years of employment as a software developer
Special Student Program, Computer Science, 5.0/5.0, Special Student Program, Computer Science, 5.0/5.0 at Massachusetts Institute of Technology
The University of Hong Kong (HKU)
High School Diploma, Straight A's, High School Diploma, Straight A's at No. 2 High School of East China Normal University
Doctor of Philosophy - PhD, Artificial Intelligence, Doctor of Philosophy - PhD, Artificial Intelligence at Max Planck Institute
English, German, Chinese, Chinese, Japanese, Shanghainese