PhD at Max Planck Institute & ETH Zürich (2020-)
📭 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 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]
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.
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 :).
[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 will be 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.
- Aug 14, 2021: I gave 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.
- Aug 3, 2021: ACL 2021 BoF/Meetup – NLP for Social Good hosted by Alex Cristia, Mrinmaya Sachan, Rada Mihalcea, Sam Bowman, Zhijing Jin. Gather town link is on Underline [NLP4SG Homepage]
- July 15, 2021: I delivered a talk at CyberValley, Germany on “AI/NLP for Social Good.” I will overview existing directions on AI for social good, and promising new research direction to pursue (see our paper on NLP4SG). Register link: https://lnkd.in/dJN2fRQ
- June 8, 2021: I hosted a meet-up session on NLP for Social Good at CHAI Workshop@Berkeley (private event as last year; email me for the link if interested in attending).
- June 7, 2021: I gave a talk about advice on grad school applications at BrainSTEM & HKU-Robomaster (Zoom recording from 51’00 in English: here, password: 7h1B*VZm).
- May 7, 2021: I co-organized the RobustML workshop at ICLR 2021! Invited speakers include Percy Liang, Ece Kamar, etc.
- 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+.
- Dec 12, 2020: Our RobustAI workshop is accepted to ICLR 2021!
- Dec 6-11, 2020: I attended NeurIPS, and COLING. Happy to grab a chat!
- Nov 21, 2020: We achieved the 1st place at the INLG 2020 workshop, WebNLG+. Plus, our second paper, CycleGT, is admitted to the workshop too.
- Nov 17, 2020: Our ABSA robustness paper is presented at EMNLP 2020!
- Nov 7, 2020: Our 1st workshop on NLP for Positive Impact is accepted to ACL@2021!
- Sept 30, 2020: 1 paper accepted to COLING 2020: GenWiki, an unsupervised graph-to-text dataset with 1.3M data.
- 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