Zining Zhu (朱子宁)
I am a PhD student at University of Toronto. My long-term goal is to build reliable and interpretable NLP systems that can stably deploy across domains. I am interested in understanding the mechanisms and abilities of neural NLP systems to encode and use knowledge with language as a medium. Following are some ongoing projects:
| University of Toronto 2019 - 2024 (Expected)
Ph.D student in Computer Science
Advisor: Frank Rudzicz
|University of Toronto 2014 - 2019
Bachelor in Engineering Science, Robotics option.
| Amazon, Applied Scientist Intern, 2022
Search - Query Understanding.
| Tencent Jarvis Lab, Machine Learning Engineering Intern, 2019
Neural language models and pre-training techniques. Advisor: Ruihui Zhao.
|Winterlight Labs, Research Software Engineer, 2017 - 2018
Automatic detection of dementia from narrative speeches. Advisor: Jekaterina Novikova.
|TripAdvisor, Software Engineering Intern, 2017
Android applications and Java API.
|Dynamic Systems Lab at UTIAS, Research Assistant, 2016
Enhancing drone controllers using deep neural networks. Advisor: Angela Schoellig.
- ECE1786 (Toronto) Creative Applications for NLP - prep TA & TA - Summer & Fall 2022
- CSC401/2511 (Toronto) Natural Languages Computing - Co-instructor - Winter 2022
- CSC2515 (Toronto) Introduction to Machine Learning - TA - Fall 2021
- CSCC24 (Toronto) Principles of Programming Languages - TA - Summer 2021
- CSC148 (Toronto) Introduction to Computer Science - TA - Summer 2021
- CSC401/2511 (Toronto) Natural Languages Computing - TA - Winter 2021
- CSC309 (Toronto) Web Programming - TA - Fall 2020
- CSC401/2511 (Toronto) Natural Languages Computing - TA - Winter 2020
- ECE324 (Toronto) Introduction to Machine Intelligence - TA - Fall 2019
- CSC180 (Toronto) Introduction to Computer Science - TA - Fall 2016
- Reviewing for conferences: ACL Rolling Review (2021 November, 2022 January, 2022 April), ACL (2020-2021), EMNLP (2020 - 2021), NAACL (2021), AAAI (2021), ICLR (2022), NeurIPS (2022)
- Reviewing for workshops: LT-EDI (2022), CMCL (2022)
- Reviewing for journals:
- IEEE Journal of Biomedical and Health Informatics
- Computer Methods & Programs in Biomedicine
- Ontario Graduate Scholarship, Provincial, 2022
- Vector Institute Research Grant, Institutional, 2020, 2021
- Dean’s List, Institutional, undergraduate years 2014 - 2019
- Engineering Science Research Opportunity Program (ESROP) fellowship, Institutional, 2016 summer
- Chinese Physics Olympics (CPhO) 1st Prize, Provincial, 2013
- Invited talk. Incorporating probing in the development of large language models, Vector Institute Endless Summer School (ESS), March 1, 2022
- Invited talk. Probing neural language models, AISC Recent Advances in NLP talk, Aug 15, 2021
- 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
- TechXplore, A new machine learning model to isolate the effects of age in predicting dementia July 27, 2018
- Marvin Minsky is my great-great-grand advisor (Z Zhu to F Rudzicz to G Hirst to E Charniak to M Minsky)
- I post videos on YouTube channel, and this blog.
- Notes about some AI / NLP conferences.
NAACL’18 NAACL’19 AAAI ‘20 ACL ‘20, NAACL ‘21
- I paddled at dragonboat teams: Iron Dragons (2018-2019 season) and Vic Scarlet Dragons (2017-2018 season).