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Chunchuan Lyu

Assistant Professor

20132026

Research activity per year

Personal profile

Personal profile

Chunchuan started his research at XJTLU working on adversarial example. After he moved to Edinburgh, he has been researching on natual language processing, in particular computational semantics. During his PhD years, he has interned at Amazon and IBM. During his postdoc at Lisbon, he focused on structured prediction. Now, his main interest is unsupervised reinforcement learning. Clearly, he is a person that favors exploring new ideas.

Research interests

Structured Prediction

Natural Language Processing

Reinforcement Learning

Experience

Postdoc at Instituto Superior Técnico at Lisbon 2021-2022

Lecturer at Department of Intelligence 2023-now

Teaching

INT 201 Decision, Computation and Language

INT 202 Complexity of Algorithms

INT 405 Natural Language Processing

Awards and honours

10-Year Highest-Impact Paper Award ICDM 2024

Education/Academic qualification

Bachelor, Xi'an Jiaotong-Liverpool University 2011-2015

Msc, University of Edinburgh 2015-2016

PhD, University of Edinburgh 2016-2021

Research areas

  • Reinforcement learning
  • Natural Language Processing (NLP)
  • Machine Learning
  • Uncertainty Quantification

Keywords

  • Q Science (General)
  • Intelligent Science
  • Unsupervised Exploration

Person Types

  • Staff

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Collaborations and top research areas from the last five years

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  • 8 Conference Proceeding
  • 1 Article
  • 1 Editorial

  • DeepSPIN: Deep Structured Prediction for Natural Language Processing

    Martins, A. F. T., Peters, B., Zerva, C., Lyu, C., Correia, G., Treviso, M., Martins, P. & Mihaylova, T., 2022, EAMT 2022 - Proceedings of the 23rd Annual Conference of the European Association for Machine Translation. Macken, L., Rufener, A., Van den Bogaert, J., Daems, J., Tezcan, A., Vanroy, B., Fonteyne, M., Barrault, L., Costa-Jussa, M. R., Kemp, E., Pilos, S., Declercq, C., Declercq, C., Koponen, M., Forcada, M. L., Scarton, C. & Moniz, H. (eds.). European Association for Machine Translation, p. 327-328 2 p. (EAMT 2022 - Proceedings of the 23rd Annual Conference of the European Association for Machine Translation).

    Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

  • Introduction

    Vlachos, A., Agrawal, P., Martins, A., Lampouras, G. & Lyu, C., 2022, In: SPNLP 2022 - 6th Workshop on Structured Prediction for NLP, Proceedings of the Workshop. p. II

    Research output: Contribution to journal › Editorial

  • Nonparametric Learning of Two-Layer ReLU Residual Units

    Wang, Z., He, L., Lyu, C. & Cohen, S. B., 1 Nov 2022, In: Transactions on Machine Learning Research. 2022-November

    Research output: Contribution to journal › Article › peer-review

  • A Differentiable Relaxation of Graph Segmentation and Alignment for AMR Parsing

    Lyu, C., Cohen, S. B. & Titov, I., 2021, EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings. Association for Computational Linguistics (ACL), p. 9075-9091 17 p. (EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings).

    Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

    Open Access
    4 Citations (Scopus)

  • Exploiting Large-Scale Teacher-Student Training for On-Device Acoustic Models

    Liu, J., Swaminathan, R. V., Parthasarathi, S. H. K., Lyu, C., Mouchtaris, A. & Kunzmann, S., 2021, Text, Speech, and Dialogue - 24th International Conference, TSD 2021, Proceedings. Ekštein, K., Pártl, F. & Konopík, M. (eds.). Springer Science and Business Media Deutschland GmbH, p. 413-424 12 p. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); vol. 12848 LNAI).

    Research output: Chapter in Book or Report/Conference proceeding › Conference Proceeding › peer-review

    5 Citations (Scopus)
View all 10 research outputs
  • 1 Completed SURF Project
  • 1 Invited talk