Professor Tim Baldwin

  • Room: Level: 08 Room: 8.21
  • Building: Doug McDonell Building
  • Campus: Parkville

Research interests

  • Natural Language Processing (Text mining, social media analytics, text anallytics)

Personal webpage

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

Biography

Prof Timothy Baldwin is a Professor in the School of Computing and Information Systems, The University of Melbourne, Director of the ARC Training Centre in Cognitive Computing for Medical Technologies, and Associate Dean Research Training in the Melbourne School of Engineering. He was an ARC Future Fellow from 2013 to 2016, and has previously held visiting positions at Cambridge University, the University of Washington, University of Tokyo, Saarland University, and NTT Communication Science Laboratories. His research interests include text mining of social media, deep learning, computational lexical semantics, information extraction, and web mining. Tim completed a BSc(CS/Maths) and BA(Linguistics/Japanese) at The University of Melbourne in 1995, and an MEng(CS) and PhD(CS) at the Tokyo Institute of Technology in 1998 and 2001, respectively. Prior to commencing his current position at The University of Melbourne, he was a Senior Research Engineer at the Center for the Study of Language and Information, Stanford University (2001-2004).

Recent publications

  1. 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 - WWW '17 Companion. International World Wide Web Conferences Steering Committee. 2019, pp. 841-842. DOI: 10.1145/3041021.3054224
  2. Salehi, B.; Spina, D.; Moffat, A.; Sadeghi, S.; Scholer, F.; Baldwin, T.; Cavedon, L.; Sanderson, M.; Wong, W.; Zobel, J. A Living Lab Study of Query Amendment in Job Search. The 41st International ACM SIGIR Conference on Research & Development in Information Retrieval - SIGIR '18. ASSOC COMPUTING MACHINERY. 2018, pp. 905-908. DOI: 10.1145/3209978.3210082
  3. Mccaughey, T.; Budden, DM.; Sanfilippo, PG.; Gooden, GEC.; Fan, L.; Fenwick, E.; Rees, G.; Macgregor, C.; Si, L.; Chen, C.; Liang, HH.; Pebay, A.; Baldwin, T.; Hewitt, AW. A Need for Better Understanding Is the Major Determinant for Public Perceptions of Human Gene Editing. Human Gene Therapy. MARY ANN LIEBERT, INC. 2018, Vol. 30, Issue 1, pp. 36-43. DOI: 10.1089/hum.2018.033
  4. Spina, D.; Maistro, M.; Ren, Y.; Sadeghi, S.; Wong, W.; Baldwin, T.; Cavedon, L.; Moffat, A.; Sanderson, M.; Scholer, F.; Zobel, J. A preliminary comparison of job, talent, and web search. CEUR Workshop Proceedings. CEUR Workshop Proceedings. 2018, Vol. 2140.
  5. 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.
  6. Lau, JH.; Cohn, T.; Baldwin, T.; Brooke, J.; Hammond, A. Deep-speare: A joint neural model of poetic language, meter and rhyme. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, Melbourne, Australia, July 15-20, 2018, Volume 1: Long Papers. ACL Anthology. 2018, Vol. 1, pp. 1948-1958.
  7. Hoogeveen, D.; Bennett, A.; Li, Y.; Verspoor, KM.; Baldwin, T. Detecting misflagged duplicate questions in community question-answering archives. 12th International AAAI Conference on Web and Social Media, ICWSM 2018. AAAI Press. 2018, pp. 112-120.
  8. 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.
  9. Salehi, B.; Liu, F.; Baldwin, T.; Wong, W. Multitask learning for query segmentation in job search. Proceedings of the 2018 ACM SIGIR International Conference on Theory of Information Retrieval - ICTIR '18. ACM Press. 2018, pp. 179-182. DOI: 10.1145/3234944.3234965
  10. Liu, F.; Cohn, T.; Baldwin, T. Narrative modeling with memory chains and semantic supervision. 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. 278-284.
  11. 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.
  12. Rahimi, A.; Cohn, T.; Baldwin, T. Semi-supervised user geolocation via graph convolutional networks. Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, Melbourne, Australia, July 15-20, 2018, Volume 1: Long Papers. ACL. 2018, Vol. 1, pp. 2009-2019.
  13. Breen, J.; Baldwin, T.; Bond, F. The company they keep: Extracting Japanese neologisms using language patterns. GWC 2018 - 9th Global WordNet Conference. Association for Computational Linguistics. 2018, Vol. 2018-January.
  14. Li, Y.; Baldwin, T.; Cohn, T. Towards robust and privacy-preserving text representations. 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. 25-30.
  15. Hoogeveen, D.; Wang, L.; Baldwin, T.; Verspoor, KM. Web forum retrieval and text analytics: A survey. Foundations and Trends® in Information Retrieval. Now Publishers. 2018, Vol. 12, Issue 1, pp. 1-167. DOI: 10.1561/1500000062
  16. 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.
  17. Rahimi, A.; Cohn, T.; Baldwin, T. A neural model for user geolocation and lexical dialectology. Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers). ACL Anthology. 2017, Vol. 2, pp. 209-216. DOI: 10.18653/v1/P17-2033
  18. Graham, Y.; Baldwin, T.; Moffat, A.; Zobel, J. Can machine translation systems be evaluated by the crowd alone. Natural Language Engineering. CAMBRIDGE UNIV PRESS. 2017, Vol. 23, Issue 1, pp. 3-30. DOI: 10.1017/S1351324915000339
  19. Liu, F.; Baldwin, T.; Cohn, T. Capturing Long-range Contextual Dependencies with Memory-enhanced Conditional Random Fields. Proceedings of the Eighth International Joint Conference on Natural Language Processing, IJCNLP 2017, Taipei, Taiwan, November 27 - December 1, 2017 - Volume 1: Long Papers. ACL Anthology. 2017, Vol. abs/1709.03637, pp. 555-565.
  20. Vylomova, E.; Cotterell, R.; Baldwin, T.; Cohn, T. Context-aware prediction of derivational word-forms. Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017, Valencia, Spain, April 3-7, 2017, Volume 2: Short Papers. Unknown. 2017, Vol. 2, pp. 118-124.

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