John W. Sheppard

2.7k total citations
205 papers, 1.7k citations indexed

About

John W. Sheppard is a scholar working on Artificial Intelligence, Control and Systems Engineering and Software. According to data from OpenAlex, John W. Sheppard has authored 205 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 91 papers in Artificial Intelligence, 78 papers in Control and Systems Engineering and 39 papers in Software. Recurrent topics in John W. Sheppard's work include Engineering and Test Systems (62 papers), Bayesian Modeling and Causal Inference (28 papers) and Fault Detection and Control Systems (27 papers). John W. Sheppard is often cited by papers focused on Engineering and Test Systems (62 papers), Bayesian Modeling and Causal Inference (28 papers) and Fault Detection and Control Systems (27 papers). John W. Sheppard collaborates with scholars based in United States, Australia and United Kingdom. John W. Sheppard's co-authors include William R. Simpson, M. Kaufman, M.H. Nehrir, Kaveh Dehghanpour, Joseph A. Shaw, R. A. A. Morrall, Steven L. Salzberg, Patrick Donnelly, Brian Haberman and Rachel M. Green and has published in prestigious journals such as IEEE Transactions on Power Systems, Sensors and IEEE Transactions on Smart Grid.

In The Last Decade

John W. Sheppard

193 papers receiving 1.6k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John W. Sheppard United States	21	653	483	267	249	222	205	1.7k
Abhishek Dubey United States	22	479 0.7×	411 0.9×	424 1.6×	113 0.5×	61 0.3×	231	2.2k
Naruemon Wattanapongsakorn Thailand	17	122 0.2×	367 0.8×	178 0.7×	164 0.7×	54 0.2×	90	1.1k
Huan Xu United States	15	234 0.4×	124 0.3×	186 0.7×	75 0.3×	141 0.6×	51	1.0k
Ernesto Kofman Argentina	22	1.1k 1.6×	103 0.2×	462 1.7×	119 0.5×	61 0.3×	89	2.2k
Edison Pignaton de Freitas Brazil	28	385 0.6×	398 0.8×	653 2.4×	46 0.2×	88 0.4×	219	2.9k
Tag Gon Kim South Korea	18	327 0.5×	242 0.5×	95 0.4×	178 0.7×	17 0.1×	135	1.7k
Vitaly Levashenko Slovakia	20	156 0.2×	239 0.5×	130 0.5×	243 1.0×	28 0.1×	105	1.2k
Yuchang Mo China	18	169 0.3×	270 0.6×	278 1.0×	275 1.1×	129 0.6×	45	1.3k
José M. Girón-Sierra Spain	17	346 0.5×	337 0.7×	86 0.3×	27 0.1×	44 0.2×	145	1.4k
Chidchanok Lursinsap Thailand	21	82 0.1×	766 1.6×	317 1.2×	61 0.2×	55 0.2×	149	1.6k

Countries citing papers authored by John W. Sheppard

Since Specialization

Citations

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

Fields of papers citing papers by John W. Sheppard

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John W. Sheppard. 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 John W. Sheppard. The network helps show where John W. Sheppard may publish in the future.

Co-authorship network of co-authors of John W. Sheppard

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

All Works

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20 of 20 papers shown

Sheppard, John W., et al.. (2024). Identifying Hierarchical Community Structures in Content-Based Scholarly Social Networks. 440–447.

Sheppard, John W., et al.. (2023). Evolving Intertask Mappings for Transfer in Reinforcement Learning. 1. 1–8. 1 indexed citations

Sheppard, John W., et al.. (2020). Reduced-cost hyperspectral convolutional neural networks. Journal of Applied Remote Sensing. 14(3). 5 indexed citations

Sheppard, John W., et al.. (2019). Spatially Biased Random Forests.. The Florida AI Research Society. 20–25. 1 indexed citations

Sheppard, John W., et al.. (2019). Compact structures for continuous time Bayesian networks. International Journal of Approximate Reasoning. 109. 19–41.

Sheppard, John W., et al.. (2018). Evaluating Spatial Generalization of Stacked Autoencoders in Wind Vector Determination.. The Florida AI Research Society. 68–73. 1 indexed citations

Sheppard, John W., et al.. (2016). Deriving Prognostic Continuous Time Bayesian Networks from Fault Trees. Annual Conference of the PHM Society. 8(1). 4 indexed citations

Sheppard, John W., et al.. (2016). A Noisy-OR Model for Continuous Time Bayesian Networks.. The Florida AI Research Society. 668–673. 5 indexed citations

Sheppard, John W., et al.. (2015). Hierarchical Fuzzy Spectral Clustering in Social Networks using Spectral Characterization.. The Florida AI Research Society. 305–310. 3 indexed citations

10.

Wang, Caisheng, Carol J. Miller, M.H. Nehrir, John W. Sheppard, & Shawn P. McElmurry. (2014). A load profile management integrated power dispatch using a Newton-like particle swarm optimization method. Sustainable Computing Informatics and Systems. 8. 8–17. 6 indexed citations

11.

Sheppard, John W., et al.. (2014). Factored Performance Functions with Structural Representation in Continuous Time Bayesian Networks. The Florida AI Research Society. 5 indexed citations

12.

Sheppard, John W., et al.. (2014). Inference complexity in continuous time Bayesian networks. Uncertainty in Artificial Intelligence. 772–779. 10 indexed citations

13.

Schuh, Michael A., et al.. (2013). Cluster Analysis for Optimal Indexing. The Florida AI Research Society. 1 indexed citations

14.

Schuh, Michael A., Rafal A. Angryk, & John W. Sheppard. (2012). Evolving Kernel Functions with Particle Swarms and Genetic Programming. The Florida AI Research Society. 7 indexed citations

15.

Angryk, Rafal A., et al.. (2012). Automated Weather Sensor Quality Control.. The Florida AI Research Society. 7 indexed citations

16.

Sheppard, John W., et al.. (2010). Extracting Decision Trees from Diagnostic Bayesian Networks to Guide Test Selection. Annual Conference of the PHM Society. 2(1). 3 indexed citations

17.

Sheppard, John W., et al.. (2007). Offline and Online Evolutionary Bi-Directional RRT Algorithms for Efficient Re-Planning in Dynamic Environments. 1131–1136. 26 indexed citations

18.

Kaufman, M. & John W. Sheppard. (1999). P1522: a formal standard for testability and diagnosability measures. 411–418. 1 indexed citations

19.

Sheppard, John W. & Steven L. Salzberg. (1995). Combining Genetic Algorithms with Memory Based Reasoning. international conference on Genetic algorithms. 452–459. 14 indexed citations

20.

Morrall, R. A. A. & John W. Sheppard. (1981). Ascochyta blight of lentils in western Canada: 1978 to 1980. 61(1). 7–13. 43 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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