PhD at Max Planck Institute & ETH Zürich (2020-2024 expected)
📭 Email: email@example.com (If there are admin tasks I forget to reply to, please contact my secretary at firstname.lastname@example.org)
👩🎓Google Scholar / 📁CV / @ZhijingJin
I am an enthusiastic AI researcher and promoter for social good. I am a Ph.D. (started in 2020) working on two goals: (1) to expand the impact of NLP by promoting NLP for social good, and (2) to improve AI by connecting NLP with causal inference. I am supervised by Bernhard Schoelkopf at Max Planck Institute for Intelligent Systems, Germany & ETH Zürich. I am mentored by Prof Rada Mihalcea at University of Michigan, and together we promote NLP for social good and ACL Year-Round Mentorship. I am also an ELLIS PhD (<5% acceptance rate) at MPI and ETH, and my ETH co-supervisors are Prof Mrinmaya Sachan and Prof Ryan Cotterell. Previously, I was a research intern at Amazon AI (2019-2020), supervised by Prof Zheng Zhang, Prof Xipeng Qiu and Dr. David Wipf. Previously, I obtained my bachelor’s degree (1st Class Honors) from the University of Hong Kong with my bachelor thesis supervised by Prof Benjamin Kao. During undergrad, I had visiting semesters at MIT and National Taiwan University. [Here is my bio for talks; here is the list of my mentors and mentees.]
My career goal is to be a professor in NLP. My commitments are
1) Promote NLP for Social Good: See our NLP4SG initiative. Check out our position paper “How Good Is NLP?” at ACL 2021 Findings, my curated list of NLP4SG papers, and our slack. I organize the yearly workshop of NLP for Positive Impact Workshop (e.g., at ACL 2021), and I have organized the RobustML Workshop at ICLR 2021. I am also engaged in Effective Altruism, a social movement to involve people in doing good with high efficiency.
Papers: How Good Is NLP? (position paper at ACL 2021 Findings), NLP to analyze COVID policies (EMNLP 2021 Findings), NLP for healthcare (AAHPM 2020, JPSM 2020), NLP for climate change (Ongoing).
2) Connect NLP & Causality: I am the Publications Chair for the 1st conference on Causal Learning and Reasoning (CLeaR).
Papers: Causality within NLP tasks (Independent Causal Mechanism for NLP, translationese – ongoing), causality for decision-making (policy analysis, career coaching – ongoing).
3) Establish a global supportive network for NLP researchers: I co-organize the ACL Year-Round Mentorship program. I also compile a list of useful resources for career advice from undergrad, PhD to professorships in NLP/AI.
My long-term mission is to fight for all people’s reasonable access to survival and pursuit of what they love (in Chinese: 为天地立心，为生民立命，为往圣继绝学，为万世开太平). My short-term mission is to do as good research as possible, so that I won’t have any regrets in my academic career path.
Before starting my PhD (from undergrad to 2021), I spent huge efforts to get familiarized with many building blocks of NLP, including
Text Generation TextGen (6 papers on Graph-to-text generation; 3 papers on text style transfer (EMNLP 2019, ACL 2020, CL Journal 2021 survey); 2 papers on adversarial text generation (for NLP robustness Robust; AAAI 2020 oral, EMNLP 2020).
Information Extraction IE (3 papers on Relation Extraction (RE) (EMNLP 2020, AISTATS 2021, COLING 2020), 3 papers on Named Entity Recognition (NER) (NAACL 2019, Medical JPSM 2020, AAHPM 2020)).
I also have a growing interest in epistemology (the science of science and all things we do), AI for decision-making (including policy making, organizational design, and life coaching; I really like this newsletter). Feel free to contact me for interdisciplinary research.
[For research mentees] I usually supervise Master students at ETH Zürich, for at least 6-month full-time research. In very special cases, I can (remotely) mentor other research mentees with strong coding skills, and longer-than-4-month full-time commitment. If you are interested in working on NLP with me, feel free to fill in this application form, and I will contact you if we can have you remotely collaborate with ETH or UMich labs. It is unpaid w.r.t. money, but fruitful w.r.t. research experience and fun :). For non-ETH students, you can try this and this for financial support.
[Apply to our ACL Year-Round Mentorship Program] We are supporting junior researchers in NLP. You can apply as a mentee, mentor, and volunteer. By this program, you can have monthly Q&A sessions with senior NLP profs/researchers, and join a slack channel to get to know world-wide NLP researchers. I compiled a GitHub list of resources to help Global Equality for PhDs in NLP.
Organized Events & Talks
- (Upcoming, CFP in Oct 2021) I am the Publications Chair at the 1st conference on Causal Learning and Reasoning (CLeaR). Organizers include Bernhard Schölkopf, Caroline Uhler, and Kun Zhang. And Yoshua Bengio, Judea Pearl, and Max Welling will be on the advisory board.
- Oct 8, 2021: I delivered a talk on NLP for Social Good Applications: COVID Policies, Healthcare, and the Way Forward at Lakehead University, Canada, with Prof Vijay Mago and an audience of 150 people.
- Oct 4, 2021: I delivered a talk on AI for Social Good at EA Berlin, Germany, invited by Christoph Sträter.
- Sept 28, 2021: I delivered a talk on How to Self-Learn a Language by Inspirations from NLP/ML? at ELLIS Symposium 2021. (Original plan: beginner-friendly intro to GPT-3)
- Aug 14, 2021: I delivered a talk on AI for Social Good at EA unconference, Berlin, Germany.
- Aug 5, 2021: I co-organized the NLP for Positive Impact workshop at ACL-IJCNLP 2021! Invited speakers/panelists include Yejin Choi, Pascale Fung, Yulia Tsvetkov, Jason Weston, etc.
Paper Acceptance & Conference Attendance
- Aug 26, 2021: Two papers on causality+NLP accepted to EMNLP 2021! (I plan to attend EMNLP physically.)
- June 6-10, 2021: I attended NAACL 2021, CHAI Workshop@Berkeley, and ICASSP 2021. Happy to grab a chat!
- June 10, 2021: My work on NLP&Causality (independent causal mechanisms) is introduced in the Keynote of Bernhard Schoelkopf at ICASSP 2021. There will be YouTube streaming.
- May 5, 2021: My first-author paper on NLP for Social Good is accepted to Findings of ACL 2021!
- Jan 25, 2021: Our paper on one-to-many mapping of cycle training is accepted to AISTATS 2021!
- Dec 27, 2020: I presented our EMNLP 2020 paper ABSA robustness at CSSNLP seminar.
- Dec 18, 2020: I presented two papers at the INLG 2020 workshop, WebNLG+.
- For more news, please check here.
For the .bib file of my publications, please check here.
Robust Is BERT Really Robust? A Strong Baseline for Natural Language Attack on Text Classification and Entailment
Di Jin*, Zhijing Jin*, Tianyi Joey Zhou, Peter Szolovits
AAAI 2020 (20.6%) / Paper / Code / Slides / Poster / MIT News / ACM TechNews / WeVolver / VentureBeat / Synced (Chinese)
CogSci Prediction of Story Ending with Optimistic and Pessimistic Mindsets
Zhijing Jin, Prof. Patrick Winston (1943-2019)
Tool Word Representations for Computing Semantic Relatedness
Zhijing Jin, Xiaolong Gong, Linpeng Huang
In contribution to the AAAI 2018 paper.
Tutorial & Survey
NLP Graph Neural Net Applications for Natural Language Processing
Xipeng Qiu, Zhijing Jin, Xiangkun Hu