Email: zjin@cs.toronto.edu      Research: Google Scholar | CV
Social Media: 𝕏 @ZhijingJin | 🦋 ZhijingJin (Pronounced like “G-Gin Gin”)

I am an incoming Assistant Professor at the University of Toronto starting in Fall 2025, and currently a postdoc at the Max Planck Institute with Bernhard Schoelkopf, based in Europe. I will also be a CIFAR AI Chair, ELLIS advisor, and faculty member at the Vector Institute.

My research areas are Large Language Models (LLMs), Natural Language Processing (NLP), and Causal Inference. My two main lines of research are Causal Reasoning with LLMs (Corr2Cause, CLadder, CausalQuest & Survey), and Multi-Agent LLM systems (GovSim & my talk@OECD).

My technical work focuses on causal inference methods for NLP, specifically to address robustness [1,2,3,4], interpretability [4,5], and causal/logical reasoning [6,7,8,9] of LLMs. See my Tutorial@NeurIPS 2024, Keynote@EMNLP 2023 BlackboxNLP Workshop, and Tutorial@EMNLP 2022.

I also extend the broader impact of Causal NLP to social good applications, with foundational work on the NLP for Social Good (NLP4SG) framework [10,11; MIT News], social policy analysis [12,13], gender bias [14,15], and healthcare [16,17,18]. See my Talk@EMNLP 2022 NLP for Positive Impact Workshop, and 5 related workshops I’ve co-organized.

For community service, I co-organize the ACL Year-Round Mentorship (a network of 650+ mentees and 90+ NLP mentors), and provide research guidance [19] and career suggestions.

Watch & Read