Abhinav Saxena

103 papers receiving 4.9k citations

Hit Papers

Damage propagation modeling for aircraft engine run-to-fa...20082026201420202008200820082505007501000

Peers

Abhinav Saxena
Comparison fields: 5 of 116
  • Control and Systems Engineering 2.9k
  • Safety, Risk, Reliability and Quality 1.3k
  • Mechanical Engineering 992
  • Electrical and Electronic Engineering 982
  • Automotive Engineering 919
Replace Bo‐Suk Yang with:
Bo‐Suk Yang South Korea
David He United States
Marcos E. Orchard Chile
Kamal Medjaher France
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Weiwen Peng China
Wenbin Wang China
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Bhaskar Saha United States
Abhinav Saxena relative to Bo‐Suk Yang South Korea Bo‐Suk Yang's profile →
Citations per field
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Citations per year

Countries citing papers authored by Abhinav Saxena

Since Specialization
Citations

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

Fields of papers citing papers by Abhinav Saxena

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Abhinav Saxena

This figure shows the co-authorship network connecting the top 25 collaborators of Abhinav Saxena. A scholar is included among the top collaborators of Abhinav Saxena 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 Abhinav Saxena. Abhinav Saxena 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
#WorkIndexed citations
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Accelerated Aging Experiments for Prognostics of Damage Growth in Composite Materials
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Damage propagation modeling for aircraft engine run-to-failure simulationbreakdown →
1127
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Damage Propagation Modeling for Aircraft Engine Prognostics
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Optimum Feature Selection and Extraction for Fault Diagnosis and Prognosis.
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Prognostics in the Control Loop.
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About Abhinav Saxena

Abhinav Saxena is a scholar working on Medical Laboratory Technology, Statistics, Probability and Uncertainty and Control and Systems Engineering, having authored 116 papers that have together received 5.1k indexed citations. Recurring topics across this work include Fault Detection and Control Systems (51 papers), Machine Fault Diagnosis Techniques (19 papers) and Structural Health Monitoring Techniques (16 papers). The work is most often cited by research in Safety, Risk, Reliability and Quality (1.3k citations), Control and Systems Engineering (2.9k citations) and Medical Laboratory Technology (170 citations). Abhinav Saxena has collaborated with scholars based in United States, India and Chile. Frequent co-authors include Kai Goebel, José Celaya, Bhaskar Saha, Neil Eklund, Sankalita Saha, Edward Balaban, Jon P. Christophersen, Saad Ashraf, Yongming Liu and George Vachtsevanos. Their work appears in journals such as Expert Systems with Applications, Journal of Physics D Applied Physics and American Journal of Tropical Medicine and Hygiene.

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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