Zhijing Jin
Assistant Professor at the University of Toronto
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. I work on Causal Reasoning with LLMs (Corr2Cause, CLadder, Quriosity & Survey), Multi-Agent AI Safety problems (GovSim, SanctSim & my OECD talk), Moral Reasoning in LLMs (TrolleyProblems, MoralExceptQA), Mechanistic Interpretability (CompMechs, Mem vs Reasoning), and Adversarial Attack (TextFooler, RouterAttack). My technical research contributes to AI Safety and AI for Science.
I am the recipient of 3 Rising Star awards, 2 Best Paper Awards at NeurIPS 2024 Workshops, and several fellowships at Open Philanthropy and the Future of Life Institute. My work is reported in CHIP Magazine, WIRED, and MIT News. My research is funded by NSERC, Schmidt Sciences, MPI, UofT, and Cooperative AI Foundation.
Our Jinesis AI Lab
We conduct frontier research on AI, large language models, and causal reasoning. We constantly have openings for student researchers (at UofT, ETH, UMich, and many other affiliations), and provide remote research mentorship for people in any career stage from anywhere in the world.
Check out the complete list of students and alumni on my CV.
*The Jinesis AI Lab is pronounced as “Genesis”, in memory of Prof. Patrick Winston.
Research Overview
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.
“Harness the power of AI to make the world a better place.”
Vision of the Jinesis AI Lab@UToronto
Founded in 2025
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