Daniel Hewlett

498 total citations
16 papers, 209 citations indexed

About

Daniel Hewlett is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Control and Systems Engineering. According to data from OpenAlex, Daniel Hewlett has authored 16 papers receiving a total of 209 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 7 papers in Computer Vision and Pattern Recognition and 2 papers in Control and Systems Engineering. Recurrent topics in Daniel Hewlett's work include Natural Language Processing Techniques (11 papers), Topic Modeling (10 papers) and Multimodal Machine Learning Applications (7 papers). Daniel Hewlett is often cited by papers focused on Natural Language Processing Techniques (11 papers), Topic Modeling (10 papers) and Multimodal Machine Learning Applications (7 papers). Daniel Hewlett collaborates with scholars based in United States, Netherlands and Israel. Daniel Hewlett's co-authors include Alexandre Lacoste, Illia Polosukhin, Paul R. Cohen, Eunsol Choi, Jakob Uszkoreit, Jonathan Berant, Llion Jones, David Berthelot, Jay J. Han and Matthew Kelcey and has published in prestigious journals such as Meeting of the Association for Computational Linguistics, Neural Information Processing Systems and International Joint Conference on Artificial Intelligence.

In The Last Decade

Daniel Hewlett

15 papers receiving 188 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Daniel Hewlett United States	7	192	70	27	10	7	16	209
Saloni Potdar United States	7	178 0.9×	38 0.5×	24 0.9×	8 0.8×	7 1.0×	14	209
Zheng Yong United States	6	227 1.2×	39 0.6×	17 0.6×	6 0.6×	7 1.0×	11	264
Yiping Song China	8	421 2.2×	73 1.0×	46 1.7×	9 0.9×	3 0.4×	25	445
Gema Ramírez-Sánchez Spain	8	362 1.9×	66 0.9×	27 1.0×	4 0.4×	6 0.9×	13	384
Michel Crampes France	5	47 0.2×	37 0.5×	24 0.9×	12 1.2×	6 0.9×	16	97
Filip Jurčíček United Kingdom	11	391 2.0×	51 0.7×	13 0.5×	9 0.9×	3 0.4×	24	404
Burcu Can Türkiye	9	192 1.0×	25 0.4×	44 1.6×	25 2.5×	10 1.4×	38	251
Koen Deschacht Belgium	8	239 1.2×	96 1.4×	62 2.3×	18 1.8×	5 0.7×	13	316

Countries citing papers authored by Daniel Hewlett

Since Specialization

Citations

This map shows the geographic impact of Daniel Hewlett's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Hewlett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Hewlett more than expected).

Fields of papers citing papers by Daniel Hewlett

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel Hewlett. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Hewlett. The network helps show where Daniel Hewlett may publish in the future.

Co-authorship network of co-authors of Daniel Hewlett

This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Hewlett. A scholar is included among the top collaborators of Daniel Hewlett based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Hewlett. Daniel Hewlett is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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16 of 16 papers shown

Shen, Jiacong, et al.. (2025). LinkSAGE: Optimizing Job Matching Using Graph Neural Networks. 2448–2457.

Kenter, Tom, Llion Jones, & Daniel Hewlett. (2018). Byte-Level Machine Reading Across Morphologically Varied Languages. Proceedings of the AAAI Conference on Artificial Intelligence. 32(1). 9 indexed citations

Choi, Eunsol, Daniel Hewlett, Jakob Uszkoreit, et al.. (2017). Coarse-to-Fine Question Answering for Long Documents. 209–220. 79 indexed citations

Hewlett, Daniel, Llion Jones, Alexandre Lacoste, & İzzeddin Gür. (2017). Accurate Supervised and Semi-Supervised Machine Reading for Long Documents. 2011–2020. 13 indexed citations

Hewlett, Daniel, Alexandre Lacoste, Llion Jones, et al.. (2016). WikiReading: A Novel Large-scale Language Understanding Task over Wikipedia. 49 indexed citations

Hewlett, Daniel & Paul R. Cohen. (2011). Fully Unsupervised Word Segmentation with BVE and MDL. Meeting of the Association for Computational Linguistics. 540–545. 6 indexed citations

Hewlett, Daniel & Paul R. Cohen. (2011). Word Segmentation as General Chunking. 39–47. 4 indexed citations

Walsh, Thomas J., Daniel Hewlett, & Clayton T. Morrison. (2011). Blending Autonomous Exploration and Apprenticeship Learning. Neural Information Processing Systems. 24. 2258–2266. 4 indexed citations

Hewlett, Daniel, Thomas J. Walsh, & Paul R. Cohen. (2011). Teaching and executing verb phrases. 25. 1–6. 4 indexed citations

10.

Cohen, Paul R. & Daniel Hewlett. (2011). A framework for recognizing and executing verb phrases. 2 indexed citations

11.

Hewlett, Daniel & Paul R. Cohen. (2010). Artificial General Segmentation. 2 indexed citations

12.

Hewlett, Daniel & Paul R. Cohen. (2009). Bootstrap voting experts. International Joint Conference on Artificial Intelligence. 1071–1076. 10 indexed citations

13.

Hewlett, Daniel, et al.. (2007). Wubble World. Proceedings of the AAAI Conference on Artificial Intelligence and Interactive Digital Entertainment. 3(1). 20–24. 1 indexed citations

14.

Hewlett, Daniel, et al.. (2007). Wubble World. National Conference on Artificial Intelligence. 20–24. 5 indexed citations

15.

Kerr, Wesley T., et al.. (2007). Learning in Wubble World. 15. 330–335. 5 indexed citations

16.

Parsia, Bijan, Evren Sirin, Bernardo Cuenca Grau, Edna Ruckhaus, & Daniel Hewlett. (2005). Cautiously Approaching SWRL. 16 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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