Laura Freeman

1.5k total citations
59 papers, 880 citations indexed

About

Laura Freeman is a scholar working on Artificial Intelligence, Statistics, Probability and Uncertainty and Statistics and Probability. According to data from OpenAlex, Laura Freeman has authored 59 papers receiving a total of 880 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Artificial Intelligence, 18 papers in Statistics, Probability and Uncertainty and 17 papers in Statistics and Probability. Recurrent topics in Laura Freeman's work include Probabilistic and Robust Engineering Design (13 papers), Adversarial Robustness in Machine Learning (9 papers) and Statistical Distribution Estimation and Applications (9 papers). Laura Freeman is often cited by papers focused on Probabilistic and Robust Engineering Design (13 papers), Adversarial Robustness in Machine Learning (9 papers) and Statistical Distribution Estimation and Applications (9 papers). Laura Freeman collaborates with scholars based in United States, Canada and Netherlands. Laura Freeman's co-authors include Anna Jensen, Natasha Khalife, Thomas G. O’Connor, Kieran J. O’Donnell, Vivette Glover, G. Geoffrey Vining, Stephen W. Rouhana, Andrew R. Kemper, Craig McNally and Stefan M. Duma and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Laura Freeman

45 papers receiving 851 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Laura Freeman United States 14 246 219 170 133 122 59 880
Kenneth W. Kemp United Kingdom 15 135 0.5× 77 0.4× 337 2.0× 170 1.3× 48 0.4× 49 796
Michael Ames United States 20 38 0.2× 39 0.2× 76 0.4× 114 0.9× 74 0.6× 33 1.4k
Lori A. Thombs United States 19 29 0.1× 19 0.1× 84 0.5× 219 1.6× 21 0.2× 43 1.1k
Mehdi Jabbari Nooghabi Iran 15 27 0.1× 17 0.1× 84 0.5× 137 1.0× 13 0.1× 73 652
Monique Frize Canada 20 97 0.4× 111 0.5× 7 0.0× 19 0.1× 43 0.4× 125 1.2k
Mark Werner United States 16 36 0.1× 37 0.2× 91 0.5× 170 1.3× 65 0.5× 36 795
Luciana De Michelis Mendonça Brazil 15 180 0.7× 8 0.0× 28 0.2× 183 1.4× 10 0.1× 59 1.5k
Tammy Jiang United States 12 54 0.2× 26 0.1× 11 0.1× 14 0.1× 283 2.3× 36 909
Chun‐I Chen Taiwan 19 45 0.2× 46 0.2× 6 0.0× 10 0.1× 74 0.6× 64 1.4k
Jun Shao China 7 28 0.1× 13 0.1× 36 0.2× 192 1.4× 27 0.2× 13 646

Countries citing papers authored by Laura Freeman

Since Specialization
Citations

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

Fields of papers citing papers by Laura Freeman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura Freeman

This figure shows the co-authorship network connecting the top 25 collaborators of Laura Freeman. A scholar is included among the top collaborators of Laura Freeman 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 Laura Freeman. Laura Freeman 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.
Freeman, Laura, et al.. (2025). The Impact of Generative AI on Test & Evaluation: Challenges and Opportunities. VTechWorks (Virginia Tech). 1376–1380.
2.
Adams, Stephen, et al.. (2025). Probabilistic Models for Military Kill Chains. Systems. 13(10). 924–924.
3.
Freeman, Laura, et al.. (2025). Evaluating Large Language Model Robustness using Combinatorial Testing. 300–309. 1 indexed citations
4.
5.
Cody, Tyler, Laura Freeman, & Peter A. Beling. (2024). On the role of loss-driven systems analysis in assessing AI ethics. 1–1.
6.
7.
Cody, Tyler, et al.. (2024). Leveraging Combinatorial Coverage in the Machine Learning Product Lifecycle. Computer. 57(7). 16–26. 3 indexed citations
8.
Freeman, Laura, et al.. (2023). Evaluation of Machine-Learning Data Fusion Classifier Performance for Ship-Wake Detection with Modified Data Sets. AIAA SCITECH 2023 Forum. 2 indexed citations
9.
Freeman, Laura. (2023). Review: Is design data collection still relevant in the big data era? With extensions to machine learning. Quality and Reliability Engineering International. 39(4). 1102–1106. 2 indexed citations
10.
Freeman, Laura, et al.. (2022). Improving Deep Learning for Maritime Remote Sensing through Data Augmentation and Latent Space. SHILAP Revista de lepidopterología. 4(3). 665–687. 4 indexed citations
11.
Cody, Tyler, et al.. (2022). Active Learning with Combinatorial Coverage. 10. 1129–1136. 3 indexed citations
12.
Nguyen, Minh N. H., et al.. (2022). Trustworthy AI Solutions for Cyberbiosecurity Challenges in Water Supply Systems. SHILAP Revista de lepidopterología. 35. 2 indexed citations
13.
Cody, Tyler, Peter A. Beling, & Laura Freeman. (2022). Test and Evaluation Harnesses for Learning Systems. 10. 1–6. 1 indexed citations
14.
Cody, Tyler, et al.. (2022). Combinatorial coverage framework for machine learning in multi-domain operations. 58–58. 3 indexed citations
15.
16.
Freeman, Laura, et al.. (2021). Robustness with respect to class imbalance in artificial intelligence classification algorithms. Journal of Quality Technology. 53(5). 505–525. 15 indexed citations
17.
Johnson, Thomas H., et al.. (2017). Power approximations for generalized linear models using the signal-to-noise transformation method. Quality Engineering. 30(3). 511–524. 1 indexed citations
18.
Freeman, Laura & G. Geoffrey Vining. (2011). Reliability data analysis for life test experiments with subsampling. Quality Engineering. 56(1). 151–152. 4 indexed citations
19.
Freeman, Laura & G. Geoffrey Vining. (2010). Reliability Data Analysis for Life Test Experiments with Subsampling. Journal of Quality Technology. 42(3). 233–241. 38 indexed citations
20.
Kemper, Andrew R., et al.. (2007). The Biomechanics of Human Ribs: Material and Structural Properties from Dynamic Tension and Bending Tests. SAE technical papers on CD-ROM/SAE technical paper series. 1. 115 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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