Associate Professor Trevor Cohn

  • Room: Level: 03 Room: 323
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Natural Language Processing (Translation, Text mining, Text analytics, Machine Learning)

Personal webpage

http://people.eng.unimelb.edu.au/tcohn

Biography

Trevor Cohn is an Associate Professor in the School of Computing and Information Systems, The University of Melbourne and an Australian Research Council Future Fellow. He was previously employed at the University of Sheffield and the University of Edinburgh, and has held visiting positions at the University of Melbourne and Johns Hopkins University. His research interests focus on development of probabilistic and statistical machine learning methods for modelling natural language text, with particular interests in machine translation, parsing and grammar induction. Current projects include text analytics and rumour diffusion over social media, translating diverse and noisy text sources and speech translation. He has served on the editorial boards for Computational Linguistics and Computer Speech and Language, as area chair and reviews for major conferences including ACL, EMNLP, COLING and NIPS, as well as reviewing for several grant authorities. Trevor completed a BEng(Software) and BComm(Finance) in 2000, followed by a PhD(Engineering) in 2007, all at The University of Melbourne. Prior to commencing his position at The University of Melbourne, he was a Senior Lecturer at The University of Sheffield (2009-2014).

Recent publications

  1. Spratley, S.; Beck, D.; Cohn, T. A Unified Neural Architecture for Instrumental Audio Tasks. ICASSP 2019 - 2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE. 2019, Vol. 2019-May, pp. 461-465. DOI: 10.1109/ICASSP.2019.8682765
  2. Adams, O.; Cohn, T.; Neubig, G.; Cruz, H.; Bird, S.; Michaud, A. Evaluation Phonemic Transcription of Low-Resource Tonal Languages for Language Documentation. LREC 2018 - 11th International Conference on Language Resources and Evaluation. European Language Resources Association. 2019, pp. 3356-3365.
  3. Lukasik, M.; Bontcheva, K.; Cohn, T.; Zubiaga, A.; Liakata, M.; Procter, R. Gaussian processes for rumour stance classification in social media. ACM Transactions on Information Systems. Association for Computing Machinery (ACM). 2019, Vol. 37, Issue 2, pp. 1-24. DOI: 10.1145/3295823
  4. Shivashankar, S.; Baldwin, T.; Brooke, J.; Cohn, T. Pairwise webpage coreference classification using distant supervision. Proceedings of the 26th International Conference on World Wide Web Companion, Perth, Australia, April 3-7, 2017. ACM Press. 2019, pp. 841-842. DOI: 10.1145/3041021.3054224
  5. Li, Y.; Rubinstein, BIP.; Cohn, T. Truth inference at scale: A Bayesian model for adjudicating highly redundant crowd annotations. The World Wide Web Conference on - WWW '19. ACM. 2019, pp. 1028-1038. DOI: 10.1145/3308558.3313459
  6. Cohn, T.; Schulz, P.; Aziz, W. A Stochastic Decoder for Neural Machine Translation. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). ACL Anthology. 2018, Vol. 1, pp. 1243-1252.
  7. Subramanian, S.; Baldwin, T.; Cohn, T. Content-based popularity prediction of online petitions using a deep regression model. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, Melbourne, Australia, July 15-20, 2018, Volume 2: Short Papers. ACL Anthology. 2018, Vol. 2, pp. 182-188.
  8. Pianta, MJ.; Makrai, E.; Verspoor, KM.; Cohn, TA.; Downie, LE. Crowdsourcing critical appraisal of research evidence (CrowdCARE) was found to be a valid approach to assessing clinical research quality. Journal of Clinical Epidemiology. ELSEVIER SCIENCE INC. 2018, Vol. 104, pp. 8-14. DOI: 10.1016/j.jclinepi.2018.07.015
  9. Baldwin, T.; Cohn, T.; Brooke, J.; Lau, JH.; Hammond, A. Deep-speare: A joint neural model of poetic language, meter and rhyme. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). ACL Anthology. 2018, Vol. 1, pp. 1948-1958.
  10. Zubiaga, A.; Kochkina, E.; Liakata, M.; Procter, R.; Lukasik, M.; Bontcheva, K.; Cohn, T.; Augenstein, I. Discourse-aware rumour stance classification in social media using sequential classifiers. Inf. Process. Manage.. Elsevier BV. 2018, Vol. 54, Issue 2, pp. 273-290. DOI: 10.1016/j.ipm.2017.11.009
  11. Panyam, NC.; Verspoor, K.; Cohn, T.; Ramamohanarao, K. Exploiting graph kernels for high performance biomedical relation extraction. J. Biomedical Semantics. BMC. 2018, Vol. 9, Issue 1. DOI: 10.1186/s13326-017-0168-3
  12. Cohn, T.; Haffari, G.; Beck, D. Graph-to-Sequence Learning using Gated Graph Neural Networks. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). ACL Anthology. 2018, Vol. 1, pp. 273-283.
  13. Subramanian, S.; Cohn, T.; Baldwin, T. Hierarchical Structured Model for Fine-to-Coarse Manifesto Text Analysis. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT 2018, New Orleans, Louisiana, USA, June 1-6, 2018, Volume 1 (Long Papers). Association for Computational Linguistics. 2018, pp. 1964-1974.
  14. Michaud, A.; Adams, O.; Cohn, TA.; Neubig, G.; Guillaume, S. Integrating Automatic Transcription into the Language Documcntation Workflow: Experiments with Na Data and the Persephone Toolkit. LANGUAGE DOCUMENTATION & CONSERVATION. UNIV HAWAII PRESS. 2018, Vol. 12, pp. 393-429.
  15. Hoang, CDV.; Koehn, P.; Haffari, G.; Cohn, T. Iterative Back-Translation for Neural Machine Translation. Proceedings of the 2nd Workshop on Neural Machine Translation and Generation, NMT@ACL 2018, Melbourne, Australia, July 20, 2018. ACL Anthology. 2018, pp. 18-24.
  16. Liu, F.; Cohn, T.; Baldwin, T. Narrative Modeling with Memory Chains and Semantic Supervision. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). ACL Anthology. 2018, Vol. 2, pp. 278-284.
  17. Liu, F.; Cohn, T.; Baldwin, T. Recurrent Entity Networks with Delayed Memory Update for Targeted Aspect-Based Sentiment Analysis. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT, New Orleans, Louisiana, USA, June 1-6, 2018, Volume 2 (Short Papers). Association for Computational Linguistics. 2018, pp. 278-283.
  18. Rahimi, A.; Baldwin, T.; Cohn, T. Semi-supervised User Geolocation via Graph Convolutional Networks. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). ACL. 2018, Vol. 1, pp. 2009-2019.
  19. Li, Y.; Baldwin, T.; Cohn, T. Towards Robust and Privacy-preserving Text Representations. ACL 2018 - 56th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers). ACL Anthology. 2018, Vol. 2, pp. 25-30.
  20. Li, Y.; Baldwin, T.; Cohn, T. What’s in a Domain? Learning Domain-Robust Text Representations using Adversarial Training. Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL-HLT, New Orleans, Louisiana, USA, June 1-6, 2018, Volume 2 (Short Papers). Association for Computational Linguistics. 2018, pp. 474-479.

View a full list of publications on the University of Melbourne’s ‘Find An Expert’ profile