Laura E. Brown

3.0k total citations · 1 hit paper
41 papers, 1.9k citations indexed

About

Laura E. Brown is a scholar working on Artificial Intelligence, Electrical and Electronic Engineering and Control and Systems Engineering. According to data from OpenAlex, Laura E. Brown has authored 41 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 9 papers in Electrical and Electronic Engineering and 6 papers in Control and Systems Engineering. Recurrent topics in Laura E. Brown's work include Bayesian Modeling and Causal Inference (9 papers), Teaching and Learning Programming (5 papers) and Machine Learning and Algorithms (3 papers). Laura E. Brown is often cited by papers focused on Bayesian Modeling and Causal Inference (9 papers), Teaching and Learning Programming (5 papers) and Machine Learning and Algorithms (3 papers). Laura E. Brown collaborates with scholars based in United States, Canada and Greece. Laura E. Brown's co-authors include Ioannis Tsamardinos, Constantin Aliferis, Gordon G. Parker, Wayne W. Weaver, Lynn Mazzoleni, Simeon Schum, Alexander Statnikov, Jacqueline Dunbar‐Jacob, Judith T. Matthews and Bart Peintner and has published in prestigious journals such as Renewable Energy, IEEE Transactions on Industry Applications and Environmental Research.

In The Last Decade

Laura E. Brown

37 papers receiving 1.8k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

The max-min hill-climbing Bayesian network structure learning algorithm

2006 1.1k citations Ioannis Tsamardinos, Laura E. Brown et al. Machine Learning profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Laura E. Brown United States	14	1.0k	269	239	238	226	41	1.9k
Mourad Oussalah Finland	28	1.1k 1.1×	139 0.5×	181 0.8×	138 0.6×	197 0.9×	203	2.3k
Serdar Korukoğlu Türkiye	16	1.1k 1.1×	113 0.4×	109 0.5×	82 0.3×	195 0.9×	43	2.0k
Nevin L. Zhang Hong Kong	20	1.1k 1.1×	77 0.3×	142 0.6×	152 0.6×	210 0.9×	128	1.9k
José A. Gámez Spain	25	1.2k 1.2×	127 0.5×	84 0.4×	141 0.6×	292 1.3×	130	2.1k
Shang‐Ming Zhou United Kingdom	26	803 0.8×	187 0.7×	81 0.3×	66 0.3×	483 2.1×	95	1.9k
Francisco Fernández‐Navarro Spain	23	751 0.7×	117 0.4×	216 0.9×	61 0.3×	99 0.4×	81	1.6k
Emilio Corchado Spain	24	1.1k 1.1×	180 0.7×	218 0.9×	67 0.3×	105 0.5×	133	2.3k
Yijing Li China	14	1.4k 1.3×	109 0.4×	385 1.6×	113 0.5×	55 0.2×	54	2.4k
Subhash Bagui United States	12	1.4k 1.4×	121 0.4×	111 0.5×	176 0.7×	88 0.4×	42	2.5k
Harry Zhang United States	16	732 0.7×	113 0.4×	63 0.3×	106 0.4×	67 0.3×	39	1.6k

Countries citing papers authored by Laura E. Brown

Since Specialization

Citations

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

Fields of papers citing papers by Laura E. Brown

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Laura E. Brown

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

Brown, Laura E., et al.. (2024). WIP: MATLAB WebTA, Enhancing the bigger picture through human factors.. Papers on Engineering Education Repository (American Society for Engineering Education).

Sticklen, Jon, et al.. (2023). Extending the Usability of WebTA with Unified ASTs and Errors. Digital Commons - Michigan Tech (Michigan Technological University). 19. 1–5.

Brown, Laura E., et al.. (2023). Work-in-Progress: Preliminary Work Introducing Automated Code Critiques in First-Year Engineering MATLAB Programming. Digital Commons - Michigan Tech (Michigan Technological University). 12. 1–5. 1 indexed citations

Hayibo, Koami Soulemane, et al.. (2022). Monofacial vs Bifacial Solar Photovoltaic Systems in Snowy Environments. SSRN Electronic Journal. 5 indexed citations

Schum, Simeon, Laura E. Brown, & Lynn Mazzoleni. (2020). MFAssignR: Molecular formula assignment software for ultrahigh resolution mass spectrometry analysis of environmental complex mixtures. Environmental Research. 191. 110114–110114. 90 indexed citations

Onder, Nilufer, et al.. (2020). University Studies of Student Persistence in Engineering. 25.1401.1–25.1401.15. 1 indexed citations

Song, Zhenyu & Laura E. Brown. (2019). Multi-dimensional Evaluation of Temporal Neural Networks on Solar Irradiance Forecasting. Digital Commons - Michigan Tech (Michigan Technological University). 4192–4197. 7 indexed citations

Brown, Laura E., et al.. (2019). Machine Learning for Fine-Grained Hardware Prefetcher Control. Digital Commons - Michigan Tech (Michigan Technological University). 1–9. 10 indexed citations

Brown, Laura E., et al.. (2018). An Ontology for Solar Irradiation Forecast Models. Digital Commons - Michigan Tech (Michigan Technological University). 5 indexed citations

10.

Brown, Laura E., et al.. (2016). Representation and incorporation of clinical information in outpatient oncology prognosis using Bayesian networks and Naïve Bayes. Digital Commons - Michigan Tech (Michigan Technological University). 34. 653–658.

11.

Brown, Laura E., et al.. (2016). An Introduction to k-Means Clustering. The Cupola: Scholarship at Gettysburg College (Gettysburg College). 23 indexed citations

12.

Kuang, Wei, Laura E. Brown, & Zhenlin Wang. (2015). Transfer Learning-Based Co-Run Scheduling for Heterogeneous Datacenters. Proceedings of the AAAI Conference on Artificial Intelligence. 29(1). 2 indexed citations

13.

Brown, Ian, Gennadi Y. Sizov, & Laura E. Brown. (2015). Impact of Rotor Design on Interior Permanent-Magnet Machines With Concentrated and Distributed Windings for Signal Injection-Based Sensorless Control and Power Conversion. IEEE Transactions on Industry Applications. 52(1). 136–144. 11 indexed citations

14.

Brown, Laura E., et al.. (2015). Survey of multi-agent systems for microgrid control. Engineering Applications of Artificial Intelligence. 45. 192–203. 171 indexed citations

15.

Tsamardinos, Ioannis & Laura E. Brown. (2008). Bounding the false discovery rate in local Bayesian network learning. National Conference on Artificial Intelligence. 1100–1105. 18 indexed citations

16.

Dexheimer, Judith W., et al.. (2007). Comparing decision support methodologies for identifying asthma exacerbations.. PubMed. 129(Pt 2). 880–4. 13 indexed citations

17.

Tsamardinos, Ioannis, Alexander Statnikov, Laura E. Brown, & Constantin Aliferis. (2006). Generating realistic large bayesian networks by tiling. The Florida AI Research Society. 592–597. 13 indexed citations

18.

Tsamardinos, Ioannis, Laura E. Brown, & Constantin Aliferis. (2006). The max-min hill-climbing Bayesian network structure learning algorithm. Machine Learning. 65(1). 31–78. 1061 indexed citations breakdown →

19.

Brown, Laura E., Ioannis Tsamardinos, & Constantin Aliferis. (2005). A comparison of novel and state-of-the-art polynomial Bayesian network learning algorithms. National Conference on Artificial Intelligence. 739–745. 16 indexed citations

20.

Tsamardinos, Ioannis, et al.. (2003). Scaling-Up Bayesian Network Learning to Thousands of Variables Using Local Learning Techniques. 10 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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