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Applied Scientist Intern at Amazon AI (2019-now)
📭 Email: zhijing.jin@connect.hku.hk
📁 Google Scholar / 👩‍🎓 CV

I am an enthusiastic NLP researcher and effective altruist. I am currently doing research with Amazon AI, and I will soon start my PhD with Bernhard Schoelkopf at Max Planck Institute in Fall 2020. My dream is to be a professor and actively promote AI for social good. To this end, I am engaged in Effective Altruism, a social movement to involve people in doing good with high efficiency. Previously, I obtained my bachelor’s degree (1st Class Honors) from the University of Hong Kong. [More info]

Here is a list of topics I work on:

  • Text Generation TextGen: Text style transfer; KG-to-text generation; adversarial generation (for NLP robustness Robust).
  • Information Extraction IE: Relation Extraction (RE); Named Entity Recognition (NER).
  • Medical AI Medical: NER on clinical notes; clinical outcome prediction.
  • Causality & Language
  • I also have a growing interest in philosophy, epistemology, and how to improve the political system. Feel free to contact me for interdisciplinary research.

News

Publications

Robust Tasty Burgers, Soggy Fries: Probing Aspect Robustness in Aspect-Based Sentiment Analysis
Xiaoyu Xing*, Zhijing Jin*, Di Jin, Bingning Wang, Qi Zhang, Xuanjing Huang
EMNLP 2020 / Paper / Code

IE Relation of the Relations: A New Paradigm of the Relation Extraction Problem
Zhijing Jin*, Yongyi Yang*, Xipeng Qiu, Zheng Zhang
EMNLP 2020 / Paper / Code

TextGen Hooks in the Headline: Learning to Generate Headlines with Controlled Styles
Di Jin, Zhijing Jin, Tianyi Joey Zhou, Lisa Orii, Peter Szolovits
ACL 2020 Talk / Paper / Code / Slides

IE TextGen CycleGT: Unsupervised Graph-to-Text and Text-to-Graph Generation via Cycle Training
Qipeng Guo*, Zhijing Jin*, Xipeng Qiu, Weinan Zhang, David Wipf, Zheng Zhang
arXiv 2020 / Paper / Code

TextGen An Effective Approach to Semi-Supervised Domain Adaptation for Machine Translation
Di Jin, Zhijing Jin, Tianyi Joey Zhou, Peter Szolovits
arXiv 2020 / Paper / Code

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)
Oral Presentation

Medical An Artificial Intelligence Algorithm to Identify Documented Symptoms in Patients with Heart Failure who Received Cardiac Resynchronization Therapy
Richard Leiter, Enrico Santus, Zhijing Jin, Katherine Lee, …, Charlotta Lindvall
JPSM 2020 / Article / Code

Medical Deep Natural Language Processing to Identify Symptom Documentation in Clinical Notes for Patients with Heart Failure Undergoing Cardiac Resynchronization Therapy (CRT)
Richard Leiter*, Enrico Santus*, Zhijing Jin, Katherine Lee, …, Charlotta Lindvall
AAHPM 2020 / Paper / Code

TextGen IMaT: Unsupervised Text Attribute Transfer via Iterative Matching and Translation
Zhijing Jin*, Di Jin*, Jonas Mueller, Nicholas Matthews, Enrico Santus
EMNLP 2019 / Paper / Code

IE GraphIE: A Graph-Based Framework for Information Extraction
Yujie Qian, Enrico Santos, Zhijing Jin, Jiang Guo, Regina Barzilay
NAACL 2019 / Paper / Code

Tool 3D Traffic Simulation for Autonomous Vehicles in Unity and Python
Zhijing Jin, Tristan Swedish, Ramesh Raskar
arXiv 2018 / Paper / Code

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
Paper 2020