Michael Heilman

5.1k total citations · 1 hit paper
40 papers, 2.3k citations indexed

About

Michael Heilman is a scholar working on Artificial Intelligence, Information Systems and Developmental and Educational Psychology. According to data from OpenAlex, Michael Heilman has authored 40 papers receiving a total of 2.3k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 8 papers in Information Systems and 5 papers in Developmental and Educational Psychology. Recurrent topics in Michael Heilman's work include Natural Language Processing Techniques (23 papers), Topic Modeling (20 papers) and Advanced Text Analysis Techniques (8 papers). Michael Heilman is often cited by papers focused on Natural Language Processing Techniques (23 papers), Topic Modeling (20 papers) and Advanced Text Analysis Techniques (8 papers). Michael Heilman collaborates with scholars based in United States and Germany. Michael Heilman's co-authors include Noah A. Smith, Maxine Eskénazi, Dani Yogatama, Nitin Madnani, Dipanjan Das, Kevin Gimpel, Nathan Schneider, Brendan O’Connor, Jacob Eisenstein and Kevyn Collins‐Thompson and has published in prestigious journals such as Journal of Research in Science Teaching, Bioinspiration & Biomimetics and Educational Measurement Issues and Practice.

In The Last Decade

Michael Heilman

39 papers receiving 2.1k citations

Hit Papers

Proceedings of the 49th A... 2011 2026 2016 2021 2011 200 400 600

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Michael Heilman 1.8k 387 228 217 133 40 2.3k
Joel Tetreault 3.4k 1.8× 524 1.4× 210 0.9× 295 1.4× 113 0.8× 97 3.8k
Claudia Leacock 2.1k 1.1× 359 0.9× 262 1.1× 142 0.7× 224 1.7× 32 2.4k
Michael Gamon 3.1k 1.7× 704 1.8× 116 0.5× 224 1.0× 71 0.5× 85 3.9k
Ruslan Mitkov 1.5k 0.8× 240 0.6× 84 0.4× 107 0.5× 117 0.9× 105 1.9k
Kevyn Collins‐Thompson 1.5k 0.8× 1.0k 2.7× 358 1.6× 216 1.0× 75 0.6× 71 2.5k
Torsten Zesch 1.6k 0.9× 313 0.8× 74 0.3× 126 0.6× 72 0.5× 117 1.8k
Antal van den Bosch 2.5k 1.4× 667 1.7× 276 1.2× 172 0.8× 25 0.2× 240 3.5k
Horacio Saggion 2.6k 1.4× 359 0.9× 87 0.4× 164 0.8× 42 0.3× 172 3.0k
Jean Carletta 2.0k 1.1× 200 0.5× 133 0.6× 365 1.7× 50 0.4× 61 3.0k
Richard Tobin 653 0.4× 191 0.5× 157 0.7× 71 0.3× 102 0.8× 51 1.2k

Countries citing papers authored by Michael Heilman

Since Specialization
Citations

This map shows the geographic impact of Michael Heilman'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 Michael Heilman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Heilman more than expected).

Fields of papers citing papers by Michael Heilman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Heilman. 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 Michael Heilman. The network helps show where Michael Heilman may publish in the future.

Co-authorship network of co-authors of Michael Heilman

This figure shows the co-authorship network connecting the top 25 collaborators of Michael Heilman. A scholar is included among the top collaborators of Michael Heilman 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 Michael Heilman. Michael Heilman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Schneider, Nathan, et al.. (2018). Visualizing Topical Quotations Over Time to Understand News Discourse. Figshare. 1 indexed citations
2.
Heilman, Michael & Noah A. Smith. (2018). Rating Computer-Generated Questions with Mechanical Turk. Figshare. 35–40. 8 indexed citations
3.
Heilman, Michael & Noah A. Smith. (2018). Tree Edit Models for Recognizing Textual Entailments, Paraphrases, and Answers to Questions. Research Showcase @ Carnegie Mellon University (Carnegie Mellon University). 1011–1019. 65 indexed citations
4.
Gimpel, Kevin, Nathan Schneider, Brendan O’Connor, et al.. (2018). Part-of-Speech Tagging for Twitter: Annotation, Features, and Experiments. Figshare. 42–47. 157 indexed citations
5.
Heilman, Michael & Noah A. Smith. (2018). Good Question! Statistical Ranking for Question Generation. Figshare. 609–617. 164 indexed citations
6.
Liu, Ou Lydia, Joseph A. Rios, Michael Heilman, Libby Gerard, & Marcia C. Linn. (2016). Validation of automated scoring of science assessments. Journal of Research in Science Teaching. 53(2). 215–233. 96 indexed citations
7.
Slegers, Nathan, et al.. (2016). Beneficial aerodynamic effect of wing scales on the climbing flight of butterflies. Bioinspiration & Biomimetics. 12(1). 16013–16013. 20 indexed citations
8.
Evanini, Keelan, Michael Heilman, Xinhao Wang, & Daniel Blanchard. (2015). Automated Scoring for the "TOEFL Junior"® Comprehensive Writing and Speaking Test. Research Report. ETS RR-15-09.. ETS Research Report Series. 1 indexed citations
9.
Heilman, Michael & Nitin Madnani. (2013). ETS: Domain Adaptation and Stacking for Short Answer Scoring. Joint Conference on Lexical and Computational Semantics. 275–279. 53 indexed citations
10.
Heilman, Michael & Nitin Madnani. (2013). HENRY-CORE: Domain Adaptation and Stacking for Text Similarity. Joint Conference on Lexical and Computational Semantics. 1. 96–102. 5 indexed citations
11.
Madnani, Nitin, Michael Heilman, Joel Tetreault, & Martin Chodorow. (2012). Identifying High-Level Organizational Elements in Argumentative Discourse. North American Chapter of the Association for Computational Linguistics. 20–28. 38 indexed citations
12.
Heilman, Michael, Aoife Cahill, & Joel Tetreault. (2012). Precision Isn't Everything: A Hybrid Approach to Grammatical Error Detection. North American Chapter of the Association for Computational Linguistics. 233–241. 6 indexed citations
13.
Heilman, Michael & Nitin Madnani. (2012). ETS: Discriminative Edit Models for Paraphrase Scoring. Joint Conference on Lexical and Computational Semantics. 529–535. 13 indexed citations
14.
Gimpel, Kevin, Nathan Schneider, Brendan O’Connor, et al.. (2011). Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics. 743 indexed citations breakdown →
15.
Yogatama, Dani, Michael Heilman, Brendan O’Connor, et al.. (2011). Predicting a Scientific Community’s Response to an Article. Empirical Methods in Natural Language Processing. 29. 594–604. 29 indexed citations
16.
Smith, Noah A. & Michael Heilman. (2011). Automatic factual question generation from text. 102 indexed citations
17.
Heilman, Michael, Kevyn Collins‐Thompson, Jamie Callan, & Maxine Eskénazi. (2007). Combining Lexical and Grammatical Features to Improve Readability Measures for First and Second Language Texts. North American Chapter of the Association for Computational Linguistics. 460–467. 133 indexed citations
18.
Heilman, Michael & Maxine Eskénazi. (2007). Application of automatic thesaurus extraction for computer generation of vocabulary questions. 65–68. 14 indexed citations
19.
Scheutz, Matthias, et al.. (2005). Toward affective cognitive robots for human-robot interaction. National Conference on Artificial Intelligence. 1737–1738. 19 indexed citations
20.
Eberhard, Kathleen M., Michael Heilman, & Matthias Scheutz. (2005). An Empirical and Computational Test of Linguistic Relativity. eScholarship (California Digital Library). 27(27). 4 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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026