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Hanqi Yan

PhD student

Room CS2.33

Department of Computer Science,

University of Warwick


Google ScholarLink opens in a new window, CV (2022.09)

GitHubLink opens in a new window, TwitterLink opens in a new window

Hanqi Yan (颜寒祺) is a Ph.D. student (2020.10-) under the supervision of Prof. Yulan HeLink opens in a new window, doing Natural Language Processing, with a special focus on sentiment analysis and interpretable NLP models. Now, I am a visiting student in the Machine Learning Department at MBZUAILink opens in a new window, advised by Dr. Kun ZhangLink opens in a new window, focusing on counterfactual generation under identifiablity guarantee. Before Ph.D., I spent a great time visiting Prof. Wenjie LiLink opens in a new window at The Hong Kong Polytechnic University (summer, 2019). I finished my MSc. at Peking UniversityLink opens in a new window (2017-2020) with Prof. Chengqi ChengLink opens in a new window doing spatial data mining and my BEng. at Beihang UniversityLink opens in a new window (2013-2017).

I am focusing on interpretable NLP models and am inspired by the idea of "Align the machine knowledge and human knowledge" from the book [The alignment problemLink opens in a new window]. Generally, two ways to enlarge the overlap between machines and humans and improve mutually:

1) Transform the machine knowledge to be human-friendly. Mostly, I derive probabilistic models guided by Bayesian perspectives, equipped with modern neural architectures to understand the latent features in sentiment analysis. See HINT in document classification.

2) Inject the prior human knowledge to help build the robust and debiasing models, See LexicalAT using WordNet to adversarially train a robust sentiment classifier, KAG using knowledge to enhance emotion cause detection and alleviate the position bias in dataset, and SoftDecay to improve the anisotropic representation generated by large pretrained language model.

Selected Publications (CORE rank A/A*)
  • Teaching assistant at Peking University, Introduction to Aerospace Engineering, 2018
  • Teaching assistant at University of Warwick, Natural Language Processing 2020,2021, Web Development Technologies 2021
Professional Service

Co-Chair of AACL-IJCNLP (Student Research Workshop) 2022 [proceedings]

Conference Reviewer: EMNLP'22, EACL'23, ACL'23, UAI23'

Journal Reviewer: Neurocomputing, Transactions on Information Systems (TOIS)

Paper-Reading (updating)

Paper list with notes by myself, including:

variational inference,

prompt-based methods,

causal inference (two surveys of causal inference in machine learning and recommendation),

debiasing methods.