Timothy McJunkin

1.0k total citations
69 papers, 718 citations indexed

About

Timothy McJunkin is a scholar working on Control and Systems Engineering, Electrical and Electronic Engineering and Mechanical Engineering. According to data from OpenAlex, Timothy McJunkin has authored 69 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 31 papers in Control and Systems Engineering, 26 papers in Electrical and Electronic Engineering and 11 papers in Mechanical Engineering. Recurrent topics in Timothy McJunkin's work include Smart Grid Security and Resilience (17 papers), Power System Optimization and Stability (9 papers) and Optimal Power Flow Distribution (9 papers). Timothy McJunkin is often cited by papers focused on Smart Grid Security and Resilience (17 papers), Power System Optimization and Stability (9 papers) and Optimal Power Flow Distribution (9 papers). Timothy McJunkin collaborates with scholars based in United States and Italy. Timothy McJunkin's co-authors include Charles R. Tolle, Craig Rieger, David Gorsich, Jill R. Scott, Jake Gentle, Randall A. LaViolette, Alexander W. Abboud, David Dahl, Daphne L. Stoner and Kurt S. Myers and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, Geophysical Research Letters and IEEE Access.

In The Last Decade

Timothy McJunkin

64 papers receiving 698 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Timothy McJunkin United States 16 239 174 123 83 81 69 718
Dibo Hou China 20 50 0.2× 381 2.2× 225 1.8× 275 3.3× 112 1.4× 125 1.3k
Pingjie Huang China 19 43 0.2× 301 1.7× 126 1.0× 299 3.6× 123 1.5× 96 1.0k
Fredric M. Ham United States 9 272 1.1× 426 2.4× 56 0.5× 68 0.8× 7 0.1× 31 1.1k
Wen Wen United States 13 88 0.4× 139 0.8× 64 0.5× 241 2.9× 17 0.2× 246 1.1k
Richard Meyer United States 19 141 0.6× 311 1.8× 14 0.1× 56 0.7× 66 0.8× 99 1.3k
Yusuke Fujii Japan 20 94 0.4× 147 0.8× 19 0.2× 71 0.9× 40 0.5× 82 1.6k
J. Sevilla Spain 10 62 0.3× 356 2.0× 90 0.7× 71 0.9× 12 0.1× 33 988
Curtis F. Gerald 2 77 0.3× 113 0.6× 74 0.6× 116 1.4× 16 0.2× 3 745
Norihiro Watanabe Japan 19 285 1.2× 494 2.8× 90 0.7× 334 4.0× 19 0.2× 88 1.6k
Mahmoud Meribout United Arab Emirates 24 74 0.3× 593 3.4× 123 1.0× 349 4.2× 69 0.9× 103 1.5k

Countries citing papers authored by Timothy McJunkin

Since Specialization
Citations

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

Fields of papers citing papers by Timothy McJunkin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Timothy McJunkin

This figure shows the co-authorship network connecting the top 25 collaborators of Timothy McJunkin. A scholar is included among the top collaborators of Timothy McJunkin 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 Timothy McJunkin. Timothy McJunkin 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.
Dhulipala, Somayajulu L. N., et al.. (2025). Harnessing distributed GPU computing for generalizable graph convolutional networks in power grid reliability assessments. Energy and AI. 19. 100471–100471. 1 indexed citations
2.
Gautam, Mukesh, et al.. (2024). A Resilient Integrated Resource Planning Framework for Transmission Systems: Analysis and Optimization. Sustainability. 16(6). 2449–2449. 3 indexed citations
3.
McJunkin, Timothy, et al.. (2024). Integration of New Technology Considering the Trade-Offs Between Operational Benefits and Risks: A Case Study of Dynamic Line Rating. IEEE Transactions on Power Delivery. 40(2). 739–749.
4.
Lei, Hangtian, et al.. (2023). Operational resilience metrics for power systems with penetration of renewable resources. IET Generation Transmission & Distribution. 17(10). 2344–2355. 11 indexed citations
5.
Lei, Hangtian, et al.. (2023). Frequency Resilience Enhancement for Power Systems with High Penetration of Grid-Forming Inverters. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 9. 1–5.
6.
Lin, Linyu, et al.. (2022). Operational Resilience of Nuclear-Renewable Integrated-Energy Microgrids. Energies. 15(3). 789–789. 9 indexed citations
7.
McJunkin, Timothy, et al.. (2020). An Operational Resilience Metric for Modern Power Distribution Systems. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 334–342. 21 indexed citations
8.
Bhattarai, Bishnu, et al.. (2018). Improvement of Transmission Line Ampacity Utilization by Weather-Based Dynamic Line Rating. IEEE Transactions on Power Delivery. 33(4). 1853–1863. 78 indexed citations
9.
Smidts, Carol, et al.. (2017). Support for reactor operators in case of cyber-security threats. Transactions of the American Nuclear Society. 117. 929–932.
10.
Gentle, Jake, et al.. (2017). 3D model of dispatchable renewable energy for smart microgrid power system. 21. 1–7. 3 indexed citations
11.
McJunkin, Timothy, Craig Rieger, Brian R. Johnson, et al.. (2015). Interdisciplinary Education through “Edu-tainment”: Electric Grid Resilient Control Systems Course. 26.1012.1–26.1012.14. 9 indexed citations
12.
Linda, Ondrej, Milos Manic, & Timothy McJunkin. (2011). Anomaly detection for resilient control systems using fuzzy-neural data fusion engine. OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information). 35–41. 13 indexed citations
13.
Hinman, Nancy W., et al.. (2009). Influence of Geochemistry on Detection of Bio/Organic Signatures. LPICo. 1502. 25.
14.
Miller, Karen, et al.. (2008). Investigation into Interface Lifting Within FSW Lap Welds. University of North Texas Digital Library (University of North Texas). 1 indexed citations
15.
Dahl, David, Timothy McJunkin, & Jill R. Scott. (2007). Comparison of ion trajectories in vacuum and viscous environments using SIMION: Insights for instrument design. International Journal of Mass Spectrometry. 266(1-3). 156–165. 39 indexed citations
16.
Yan, Beizhan, et al.. (2006). Validation of fuzzy logic method for automated mass spectral classification for mineral imaging. Applied Surface Science. 253(4). 2011–2017. 17 indexed citations
17.
McJunkin, Timothy, Karen K. Miller, & Charles R. Tolle. (2006). Observations on Characterization of Defects in Coiled Tubing From Magnetic-Flux-Leakage Data. 4 indexed citations
18.
McJunkin, Timothy, et al.. (2005). Mineral identification in basalts using automated mass spectral data analysis. Geochimica et Cosmochimica Acta Supplement. 69(10). 1 indexed citations
19.
Tolle, Charles R., Timothy McJunkin, & David Gorsich. (2003). Suboptimal minimum cluster volume cover-based method for measuring fractal dimension. IEEE Transactions on Pattern Analysis and Machine Intelligence. 25(1). 32–41. 24 indexed citations
20.
Scott, Jill R., et al.. (2003). Automated Analysis of Mass Spectral Data Using Fuzzy Logic Classification. JALA Journal of the Association for Laboratory Automation. 8(2). 61–63. 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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