Neil Eklund

2.9k total citations · 1 hit paper
53 papers, 2.1k citations indexed

About

Neil Eklund is a scholar working on Control and Systems Engineering, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Neil Eklund has authored 53 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Control and Systems Engineering, 10 papers in Artificial Intelligence and 9 papers in Statistics, Probability and Uncertainty. Recurrent topics in Neil Eklund's work include Fault Detection and Control Systems (27 papers), Machine Fault Diagnosis Techniques (7 papers) and Control Systems and Identification (6 papers). Neil Eklund is often cited by papers focused on Fault Detection and Control Systems (27 papers), Machine Fault Diagnosis Techniques (7 papers) and Control Systems and Identification (6 papers). Neil Eklund collaborates with scholars based in United States and Israel. Neil Eklund's co-authors include Kai Goebel, Abhinav Saxena, P.R. Boyce, Peter Boyce, Piero P. Bonissone, Raj Subbu, Thomas R. Kiehl, Hai Qiu, Weizhong Yan and Mark S. Rea and has published in prestigious journals such as IEEE Transactions on Evolutionary Computation, Proceedings of the American Mathematical Society and Transportation Research Record Journal of the Transportation Research Board.

In The Last Decade

Neil Eklund

49 papers receiving 2.0k citations

Hit Papers

Damage propagation modeling for aircraft engine run-to-fa... 2008 2026 2014 2020 2008 250 500 750 1000
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.

  1. Damage propagation modeling for aircraft engine run-to-failure simulation
    2008 1.1k citations Abhinav Saxena, Kai Goebel et al. profile →

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Neil Eklund United States 17 1.1k 482 330 281 281 53 2.1k
Dirk Söffker Germany 25 1.2k 1.1× 181 0.4× 295 0.9× 596 2.1× 23 0.1× 278 2.8k
Hong Wang China 25 440 0.4× 224 0.5× 243 0.7× 197 0.7× 24 0.1× 154 2.3k
Pan Lu United States 23 198 0.2× 505 1.0× 471 1.4× 167 0.6× 40 0.1× 119 2.1k
Hermann Winner Germany 24 724 0.6× 508 1.1× 262 0.8× 205 0.7× 15 0.1× 160 2.8k
Fakhreddine Karray Canada 12 649 0.6× 86 0.2× 733 2.2× 218 0.8× 24 0.1× 44 2.4k
Faisal Khan Ireland 21 246 0.2× 389 0.8× 174 0.5× 350 1.2× 31 0.1× 59 2.1k
Andrea Monteriù Italy 23 982 0.9× 58 0.1× 250 0.8× 218 0.8× 36 0.1× 191 2.2k
Isis Didier Lins Brazil 16 171 0.2× 255 0.5× 120 0.4× 136 0.5× 65 0.2× 69 1.1k
Lorenzo Ciani Italy 30 567 0.5× 476 1.0× 284 0.9× 252 0.9× 15 0.1× 206 2.6k

Countries citing papers authored by Neil Eklund

Since Specialization
Citations

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

Fields of papers citing papers by Neil Eklund

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Neil Eklund

This figure shows the co-authorship network connecting the top 25 collaborators of Neil Eklund. A scholar is included among the top collaborators of Neil Eklund 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 Neil Eklund. Neil Eklund 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.
Qu, Yongzhi, et al.. (2023). An Introduction to 2023 PHM Data Challenge: The Elephant in the Room and an Analysis of Competition Results. Annual Conference of the PHM Society. 15(1).
2.
Eklund, Neil, et al.. (2013). Predictive Modeling of High-Bypass Turbofan Engine Deterioration. Annual Conference of the PHM Society. 5(1). 2 indexed citations
3.
Bolander, Nathan, et al.. (2009). Physics-based Remaining Useful Life Prediction for Aircraft Engine Bearing Prognosis. 1(1). 53 indexed citations
4.
Saxena, Abhinav, et al.. (2008). Damage propagation modeling for aircraft engine run-to-failure simulation. 1–9. 1127 indexed citations breakdown →
5.
Saxena, Abhinav, et al.. (2008). Damage Propagation Modeling for Aircraft Engine Prognostics. NASA STI Repository (National Aeronautics and Space Administration). 16 indexed citations
6.
Eklund, Neil & Xiao Hu. (2008). Intermediate feature space approach for anomaly detection in aircraft engine data. International Conference on Information Fusion. 1–7. 2 indexed citations
7.
Xue, Feng, et al.. (2008). An Instance-Based Method for Remaining Useful Life Estimation for Aircraft Engines. Journal of Failure Analysis and Prevention. 8(2). 199–206. 36 indexed citations
8.
Eklund, Neil & Xiao Hu. (2007). Multi-Scale Rank-Permutation Change Localization. 6. 1–7. 1 indexed citations
9.
Goebel, Kai, Hai Qiu, Neil Eklund, & Weizhong Yan. (2007). Modeling Propagation of Gas Path Damage. 1–8. 21 indexed citations
10.
Qiu, Hai, Neil Eklund, Weizhong Yan, et al.. (2007). Estimating Deterioration Level of Aircraft Engines. 661–667. 5 indexed citations
11.
Eklund, Neil. (2006). Using genetic algorithms to estimate confidence intervals for missing spatial data. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews). 36(4). 519–523. 9 indexed citations
12.
Bonissone, Piero P., Raj Subbu, Neil Eklund, & Thomas R. Kiehl. (2006). Evolutionary algorithms + domain knowledge = real-world evolutionary computation. IEEE Transactions on Evolutionary Computation. 10(3). 256–280. 109 indexed citations
13.
Eklund, Neil, Mark J. Embrechts, & Marc Goetschalckx. (2006). Efficient chromosome encoding and problem-specific mutation methods for the flexible bay facility layout problem. IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews). 36(4). 495–502. 15 indexed citations
14.
Goebel, Kai, et al.. (2005). Rapid detection of faults for safety critical aircraft operation. 3372–3383. 8 indexed citations
15.
16.
Narendran, Nadarajah, et al.. (2000). Just-Perceivable Color Differences between Similar Light Sources in Display Lighting Applications. Journal of the Illuminating Engineering Society. 29(2). 68–77. 8 indexed citations
17.
Eklund, Neil, et al.. (2000). Lighting and Sustained Performance. Journal of the Illuminating Engineering Society. 29(1). 116–130. 21 indexed citations
18.
Boyce, P.R., et al.. (2000). Perceptions of safety at night in different lighting conditions. Lighting Research & Technology. 32(2). 79–91. 149 indexed citations
19.
Eklund, Neil & P.R. Boyce. (1996). The Development of a Reliable, Valid, and Simple Office Lighting Survey. Journal of the Illuminating Engineering Society. 25(2). 25–40. 48 indexed citations
20.
Boyce, P.R., et al.. (1995). Minimum acceptable transmittance of glazing. Lighting Research & Technology. 27(3). 145–152. 47 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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