Zining Zhu (朱子宁)

PhD Student, University of Toronto

zining@cs.toronto.edu

Research interests: Interpretability, NLP + Society.

My long-term goal is to build reliable and trustworthy NLP systems that can be stably deployed across different domains. I am interested in understanding the mechanisms and abilities of neural NLP systems encoding and using knowledge, with language as a medium. I am also interested in the impacts of NLP systems to societies.
I write articles at this blog, and upload videos discussing NLP papers to this YouTube channel.

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Selected Publications

Show all Show selected
    2020
  • An information theoretic view on selecting linguistic probes
    Zining Zhu, Frank Rudzicz. EMNLP 2020
    paper blog bib
  • Examining the rhetorical capacities of neural language models
    Zining Zhu, Chuer Pan, Mohamed Abdalla, Frank Rudzicz. EMNLP 2020 BlackboxNLP Workshop
    paper blog bib
  • Semantic coordinates analysis reveals language changes in the AI field
    Zining Zhu, Yang Xu, Frank Rudzicz. arXiv preprint 2011.00543
    paper bib
    • 2019
  • Detecting Cognitive Impairments by Agreeing on Interpretations of Linguistic Features
    Zining Zhu, Jekaterina Novikova, Frank Rudzicz. NAACL 2019
    paper bib
  • Natural Languages Understanding by a Compositional Alignment of Word Embeddings
    Zining Zhu. Engineering Science Undergraduate Thesis (supervisor: Frank Rudzicz)
    paper blog bib
    • 2018
  • Semi-Supervised Classification by Reaching Consensus among Modalities
    Zining Zhu, Jekaterina Novikova, Frank Rudzicz. NeurIPS 2018 IRASL Workshop
    paper bib
  • Deconfounding Age Effects with Fair Representation Learning When Assessing Dementia
    Zining Zhu, Jekaterina Novikova, Frank Rudzicz. arXiv preprint 1807.07217
    paper press slides bib
  • Robuatness Against the Channel Effect in Pathological Voice Detection
    Yi-Te Hsu, Zining Zhu, Chi-Te Wang, Shih-Hau Fang, Frank Rudzicz, Yu Tsao. NeurIPS 2018 ML4H Workshop
    paper bib
    • 2017
  • Deep Neural Networks for Improved, Impromptu Trajectory Tracking of Quadrotors
    Qiyang Li, Jingxing Qian, Zining Zhu, Xuchan Bao, Mohamed K. Helwa, Angela P. Schoellig. ICRA 2017
    paper blog bib
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Experience

Education

University of Toronto 2019 - 2024 (Expected)
Ph.D student in Computer Science
Supervisor: Frank Rudzicz
University of Toronto 2014 - 2019
Bachelor in Engineering Science, Robotics option.

Work / Research

Tencent Jarvis Lab, Machine Learning Engineering Intern, May 2019 - Aug 2019
Neural language models and pre-training techniques.
Winterlight Labs, Research Software Engineer, Sep 2017 - Sep 2018
Automatic detection of dementia from narrative speeches.
TripAdvisor, Software Engineering Intern, June - Aug, 2017
Android applications and Java API.
Dynamic Systems Lab at UTIAS, Research Assistant, May - Sep, 2016
Enhancing drone controllers using deep neural networks.

Teaching

University of Toronto, as Teaching Assistant:

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Service

  • Reviewing for conferences:
    • ACL (2020, 2021)
    • EMNLP (2020)
    • NAACL (2021)
    • AAAI (2021)
  • Reviewing for journals:
    • IEEE Journal of Biomedical and Health Informatics (2020)
    • Computer Methods & Programs in Biomedicine (2018)

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Awards

  • Vector Institute PhD Fellowship, 2020
  • Dean’s List, undergraduate years 2014 - 2019
  • Engineering Science Research Opportunity Program (ESROP) fellowship, 2016 summer
  • Chinese Physics Olympics (CPhO) Provincial 1st Prize, 2013

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Selected Talks

  • Invited talk. Improving the neural NLP model performances with linguistic probes, Zhi-Yi Technology Advances in NLP talk, Nov 20, 2020
  • Invited talk. An information theoretic view on selecting linguistic probes, Tsinghua University AI TIME talk, Oct 30, 2020
  • Spotlight talk. Examining the rhetorical capacities of neural language models, Vector Institute NLP Symposium, Sep 16, 2020
  • Invited talk. RecitalBoard: Efficient pre-training methods for language modeling, Tencent Jarvis Lab, Shenzhen, China, Aug 5, 2019
  • Invited talk. Detecting cognitive impairments with machine learning, UTMIST, Toronto, Canada, Nov 20, 2018
  • Invited talk. Probabilistic Graphical Models, UTADA, Toronto, Canada, Oct 21, 2017

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Media Coverage

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Misc

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