Andrew E. Waters

2.3k total citations
27 papers, 927 citations indexed

About

Andrew E. Waters is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems. According to data from OpenAlex, Andrew E. Waters has authored 27 papers receiving a total of 927 indexed citations (citations by other indexed papers that have themselves been cited), including 14 papers in Artificial Intelligence, 9 papers in Computer Science Applications and 4 papers in Information Systems. Recurrent topics in Andrew E. Waters's work include Online Learning and Analytics (8 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers) and Machine Learning and Data Classification (5 papers). Andrew E. Waters is often cited by papers focused on Online Learning and Analytics (8 papers), Intelligent Tutoring Systems and Adaptive Learning (6 papers) and Machine Learning and Data Classification (5 papers). Andrew E. Waters collaborates with scholars based in United States, Denmark and Switzerland. Andrew E. Waters's co-authors include Richard G. Baraniuk, Andrew Lan, Lance B. Price, Aswin C. Sankaranarayanan, David M. Engelthaler, Paul Keim, Christoph Studer, Phillip J. Grimaldi, Jolene R. Bowers and Cindy M. Liu and has published in prestigious journals such as PLoS ONE, Clinical Infectious Diseases and Journal of Bacteriology.

In The Last Decade

Andrew E. Waters

26 papers receiving 871 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Andrew E. Waters United States 11 225 200 165 163 154 27 927
Sergio A. Álvarez United States 16 147 0.7× 90 0.5× 154 0.9× 152 0.9× 12 0.1× 60 1.2k
Bernd Neumann Germany 18 135 0.6× 94 0.5× 42 0.3× 329 2.0× 36 0.2× 97 1.3k
Zhihao Hao China 20 176 0.8× 128 0.6× 204 1.2× 100 0.6× 5 0.0× 48 1.3k
Róbert Busa‐Fekete Hungary 18 317 1.4× 55 0.3× 52 0.3× 474 2.9× 9 0.1× 41 1.3k
Hiroyuki Sato Japan 24 173 0.8× 248 1.2× 34 0.2× 91 0.6× 3 0.0× 113 1.8k
John Hunt United States 19 253 1.1× 290 1.4× 54 0.3× 45 0.3× 5 0.0× 62 1.4k
Hongning Wang United States 30 261 1.2× 282 1.4× 23 0.1× 1.6k 9.5× 117 0.8× 144 3.0k
Donghui Yan China 21 375 1.7× 134 0.7× 83 0.5× 289 1.8× 2 0.0× 61 1.4k
Danny Kriz̧anc United States 23 487 2.2× 14 0.1× 37 0.2× 264 1.6× 40 0.3× 145 2.1k
Hyunjin Yoon South Korea 24 780 3.5× 199 1.0× 567 3.4× 111 0.7× 5 0.0× 95 2.2k

Countries citing papers authored by Andrew E. Waters

Since Specialization
Citations

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

Fields of papers citing papers by Andrew E. Waters

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Andrew E. Waters. 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 Andrew E. Waters. The network helps show where Andrew E. Waters may publish in the future.

Co-authorship network of co-authors of Andrew E. Waters

This figure shows the co-authorship network connecting the top 25 collaborators of Andrew E. Waters. A scholar is included among the top collaborators of Andrew E. Waters 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 Andrew E. Waters. Andrew E. Waters 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.
Waters, Andrew E., et al.. (2020). The effect of linguistic modification on English as a second language (ESL) nursing student retention. International Journal of Nursing Education Scholarship. 17(1). 3 indexed citations
2.
Waters, Andrew E., et al.. (2020). Inferring Student Comprehension from Highlighting Patterns in Digital Textbooks: An Exploration in an Authentic Learning Platform.. 2674. 67–79. 4 indexed citations
3.
Grimaldi, Phillip J., Debshila Basu Mallick, Andrew E. Waters, & Richard G. Baraniuk. (2019). Do open educational resources improve student learning? Implications of the access hypothesis. PLoS ONE. 14(3). e0212508–e0212508. 51 indexed citations
4.
Stevens, Scott P., et al.. (2019). Comparison of Ranking and Rating Scales in Online Peer Assessment. 205–209. 2 indexed citations
5.
Waters, Andrew E., Phillip J. Grimaldi, Andrew Lan, & Richard G. Baraniuk. (2017). Short-Answer Responses to STEM Exercises: Measuring Response Validity and Its Impact on Learning.. Educational Data Mining. 1 indexed citations
6.
Lan, Andrew, Andrew E. Waters, Christoph Studer, & Richard G. Baraniuk. (2017). BLAh: Boolean Logic Analysis for Graded Student Response Data. IEEE Journal of Selected Topics in Signal Processing. 11(5). 754–764.
7.
Stevens, Scott P., et al.. (2016). Efficacy of peer review network structures: The effects of reciprocity and clustering. International Conference on Information Systems. 2 indexed citations
8.
Waters, Andrew E., et al.. (2015). BayesRank. 177–183. 18 indexed citations
9.
Lan, Andrew, et al.. (2015). Mathematical Language Processing. 167–176. 41 indexed citations
10.
Lan, Andrew, Andrew E. Waters, Christoph Studer, & Richard G. Baraniuk. (2014). Sparse factor analysis for learning and content analytics. arXiv (Cornell University). 15(1). 1959–2008. 87 indexed citations
11.
Waters, Andrew E., et al.. (2014). A Bayesian nonparametric approach for the analysis of multiple categorical item responses. Journal of Statistical Planning and Inference. 166. 52–66. 3 indexed citations
12.
Lan, Andrew, Christoph Studer, Andrew E. Waters, & Richard G. Baraniuk. (2013). Joint Topic Modeling and Factor Analysis of Textual Information and Graded Response Data. arXiv (Cornell University). 324–325. 3 indexed citations
13.
Lan, Andrew, Christoph Studer, Andrew E. Waters, & Richard G. Baraniuk. (2013). Tag-aware ordinal sparse factor analysis for learning and content analytics. Repository for Publications and Research Data (ETH Zurich). 90–97. 4 indexed citations
14.
Waters, Andrew E., Christoph Studer, & Richard G. Baraniuk. (2013). Bayesian pairwise collaboration detection in educational datasets. 4. 989–992. 2 indexed citations
15.
Waters, Andrew E., Andrew Lan, & Christoph Studer. (2013). Sparse probit factor analysis for learning analytics. 54. 8776–8780. 3 indexed citations
16.
Peterson, Amy, Meghan F. Davis, Kathleen G. Julian, et al.. (2012). Molecular and Phenotypic Characteristics of Healthcare- and Community-Associated Methicillin-Resistant Staphylococcus aureus at a Rural Hospital. PLoS ONE. 7(6). e38354–e38354. 13 indexed citations
17.
Waters, Andrew E., Aswin C. Sankaranarayanan, & Richard G. Baraniuk. (2011). SpaRCS: Recovering low-rank and sparse matrices from compressive measurements. Neural Information Processing Systems. 24. 1089–1097. 116 indexed citations
18.
Waters, Andrew E., Tania Contente‐Cuomo, Cindy M. Liu, et al.. (2011). Multidrug-Resistant Staphylococcus aureus in US Meat and Poultry. Clinical Infectious Diseases. 52(10). 1227–1230. 238 indexed citations
19.
Hendriksen, René S., Lance B. Price, James M. Schupp, et al.. (2011). Population Genetics of Vibrio cholerae from Nepal in 2010: Evidence on the Origin of the Haitian Outbreak. mBio. 2(4). e00157–11. 217 indexed citations
20.
Waters, Andrew E. & Volkan Cevher. (2010). Distributed bearing estimation via matrix completion. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 2590–2593. 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.

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