World's Best Scientists 2026 revealed!
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Computer Science
Australia
2025

D-Index & Metrics

Computer Science

D-Index
72
Citations
21637
World Ranking
1669
National Ranking
48

Research.com Recognitions

  • 2025 - Research.com Computer Science in Australia Leader Award
  • 2023 - Research.com Computer Science in Australia Leader Award
  • 2022 - Research.com Computer Science in Australia Leader Award

Overview

Timothy Baldwin is affiliated with the University of Melbourne in Australia. Their research primarily spans the field of Computer Science, with a focus on Artificial Intelligence and related subfields including Information Systems, Safety Research, Computer Vision and Pattern Recognition, and Sociology and Political Science.

Their research delves into several main topics, notably Topic Modeling, Natural Language Processing Techniques, Text Readability and Simplification, Authorship Attribution and Profiling, Ethics and Social Impacts of AI, Advanced Text Analysis Techniques, and Multimodal Machine Learning Applications.

Timothy Baldwin has published extensively in respected venues. Frequent publication venues include:

  • arXiv (Cornell University)
  • Transactions of the Association for Computational Linguistics
  • Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  • Leibniz-Zentrum für Informatik (Schloss Dagstuhl)

Among their notable recent papers are:

  • "IndoBERTweet: A Pretrained Language Model for Indonesian Twitter with Effective Domain-Specific Vocabulary Initialization" (2021), published in the Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  • "Factuality challenges in the era of large language models and opportunities for fact-checking" (2024), published in Nature Machine Intelligence
  • "One Country, 700+ Languages: NLP Challenges for Underrepresented Languages and Dialects in Indonesia" (2022), published in the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • "IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP" (2020), published on arXiv (Cornell University)
  • "Neural factoid geospatial question answering" (2021), published in the Journal of Spatial Information Science

Timothy Baldwin's frequent co-authors include:

  • Jey Han Lau
  • Fajri Koto
  • Preslav Nakov
  • Trevor Cohn
  • Xudong Han

In addition to articles, Baldwin has published a book titled "Automatic Language Identification in Texts" (2024), released by Morgan & Claypool Publishers.

Best Publications

  • Multiword Expressions: A Pain in the Neck for NLP

    Ivan A. Sag;Timothy Baldwin;Francis Bond;Ann A. Copestake

  • Automatic Evaluation of Topic Coherence

    David Newman;Jey Han Lau;Karl Grieser;Timothy Baldwin

  • An Empirical Evaluation of doc2vec with Practical Insights into Document Embedding Generation

    Jey Han Lau;Timothy Baldwin

  • Lexical Normalisation of Short Text Messages: Makn Sens a #twitter

    Bo Han;Timothy Baldwin

  • Machine Reading Tea Leaves: Automatically Evaluating Topic Coherence and Topic Model Quality

    Jey Han Lau;David Newman;Timothy Baldwin

  • langid.py: An Off-the-shelf Language Identification Tool

    Marco Lui;Timothy Baldwin

  • SemEval-2010 Task 5 : Automatic Keyphrase Extraction from Scientific Articles

    Su Nam Kim;Olena Medelyan;Min-Yen Kan;Timothy Baldwin

  • Shared Tasks of the 2015 Workshop on Noisy User-generated Text: Twitter Lexical Normalization and Named Entity Recognition

    Timothy Baldwin;Marie Catherine de Marneffe;Bo Han;Young-Bum Kim

  • Text-based twitter user geolocation prediction

    Bo Han;Paul Cook;Timothy Baldwin

  • SemEval-2017 Task 3: Community Question Answering

    Preslav Nakov;Doris Hoogeveen;Lluís Màrquez;Alessandro Moschitti

  • Automatic Labelling of Topic Models

    Jey Han Lau;Karl Grieser;David Newman;Timothy Baldwin

  • An Empirical Model of Multiword Expression Decomposability

    Timothy Baldwin;Colin Bannard;Takaaki Tanaka;Dominic Widdows

  • How Noisy Social Media Text, How Diffrnt Social Media Sources?

    Timothy Baldwin;Paul Cook;Marco Lui;Andrew MacKinlay

  • On-line Trend Analysis with Topic Models: #twitter Trends Detection Topic Model Online

    Jey Han Lau;Nigel Collier;Timothy Baldwin

  • IndoLEM and IndoBERT: A Benchmark Dataset and Pre-trained Language Model for Indonesian NLP

    Fajri Koto;Afshin Rahimi;Jey Han Lau;Timothy Baldwin

  • Evaluating topic models for digital libraries

    David Newman;Youn Noh;Edmund Talley;Sarvnaz Karimi

  • Geolocation Prediction in Social Media Data by Finding Location Indicative Words

    Bo Han;Paul Cook;Timothy Baldwin

  • Automatically Constructing a Normalisation Dictionary for Microblogs

    Bo Han;Paul Cook;Timothy Baldwin

  • Lexical normalization for social media text

    Bo Han;Paul Cook;Timothy Baldwin

  • Tangled up in BLEU: Reevaluating the Evaluation of Automatic Machine Translation Evaluation Metrics

    Nitika Mathur;Timothy Baldwin;Trevor Cohn

  • Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing

    David Yarowsky;Timothy Baldwin;Anna Korhonen;Karen Livescu

  • Continuous Measurement Scales in Human Evaluation of Machine Translation

    Yvette Graham;Timothy Baldwin;Alistair Moffat;Justin Zobel

Frequent Co-Authors

Trevor Cohn
Trevor Cohn University of Melbourne
Karin Verspoor
Karin Verspoor RMIT University
Justin Zobel
Justin Zobel University of Melbourne
Alistair Moffat
Alistair Moffat University of Melbourne
Dan Flickinger
Dan Flickinger Stanford University
Diana McCarthy
Diana McCarthy University of Cambridge
Min-Yen Kan
Min-Yen Kan National University of Singapore
Alex W. Hewitt
Alex W. Hewitt University of Tasmania
Steven Bird
Steven Bird Charles Darwin University
James R. Gilkerson
James R. Gilkerson University of Melbourne

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