Samir Khan

1.9k total citations · 2 hit papers
43 papers, 1.4k citations indexed

About

Samir Khan is a scholar working on Control and Systems Engineering, Safety, Risk, Reliability and Quality and Statistics, Probability and Uncertainty. According to data from OpenAlex, Samir Khan has authored 43 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Control and Systems Engineering, 10 papers in Safety, Risk, Reliability and Quality and 8 papers in Statistics, Probability and Uncertainty. Recurrent topics in Samir Khan's work include Fault Detection and Control Systems (13 papers), Reliability and Maintenance Optimization (8 papers) and Risk and Safety Analysis (8 papers). Samir Khan is often cited by papers focused on Fault Detection and Control Systems (13 papers), Reliability and Maintenance Optimization (8 papers) and Risk and Safety Analysis (8 papers). Samir Khan collaborates with scholars based in United Kingdom, Japan and United States. Samir Khan's co-authors include Takehisa Yairi, John Ahmet Erkoyuncu, Richard McWilliam, Paul S Phillips, Ian Jennions, Michael Farnsworth, Takehisa Yairi, Rajkumar Roy, Shinichi Nakasuka and Seiji Tsutsumi and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Cleaner Production and Biometrika.

In The Last Decade

Samir Khan

39 papers receiving 1.3k citations

Hit Papers

A review on the application of deep learning in system he... 2018 2026 2020 2023 2018 2025 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samir Khan United Kingdom 15 662 311 221 206 203 43 1.4k
Hongfu Zuo China 20 747 1.1× 495 1.6× 314 1.4× 105 0.5× 297 1.5× 163 1.7k
Huawei Wang China 17 653 1.0× 354 1.1× 156 0.7× 132 0.6× 224 1.1× 67 1.1k
Ian Jennions United Kingdom 26 703 1.1× 417 1.3× 278 1.3× 188 0.9× 153 0.8× 147 2.0k
Chaoqun Duan China 18 322 0.5× 333 1.1× 314 1.4× 139 0.7× 100 0.5× 60 1.4k
Andrew Hess United States 16 1.2k 1.8× 336 1.1× 393 1.8× 186 0.9× 238 1.2× 47 1.7k
Liangwei Zhang China 13 575 0.9× 289 0.9× 88 0.4× 290 1.4× 143 0.7× 41 1.1k
Fateme Dinmohammadi United Kingdom 12 550 0.8× 266 0.9× 222 1.0× 104 0.5× 140 0.7× 28 1.2k
Andrew Starr United Kingdom 21 379 0.6× 486 1.6× 153 0.7× 146 0.7× 303 1.5× 119 1.7k
Kamran Javed Pakistan 14 550 0.8× 331 1.1× 205 0.9× 145 0.7× 154 0.8× 36 1.2k
Khanh T.P. Nguyen France 16 573 0.9× 222 0.7× 391 1.8× 90 0.4× 163 0.8× 57 1.1k

Countries citing papers authored by Samir Khan

Since Specialization
Citations

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

Fields of papers citing papers by Samir Khan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samir Khan

This figure shows the co-authorship network connecting the top 25 collaborators of Samir Khan. A scholar is included among the top collaborators of Samir Khan 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 Samir Khan. Samir Khan 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.
Liu, Changhao, et al.. (2025). Neuromorphic computing-enabled generalized machine fault diagnosis with dynamic vision. Advanced Engineering Informatics. 65. 103300–103300. 24 indexed citations breakdown →
2.
Khan, Samir, et al.. (2024). Waste 4.0: transforming medical waste management through digitalization and automated segregation. SHILAP Revista de lepidopterología. 5(1). 2 indexed citations
3.
Khan, Samir, et al.. (2024). An Investigation on Utilizing Large Language Model for Industrial Computer-Aided Design Automation. Procedia CIRP. 128. 221–226. 9 indexed citations
4.
Khan, Samir, et al.. (2024). Framework for Data‒Driven Fault Diagnosis of Numerical Spacecraft Propulsion Systems. International Journal of Prognostics and Health Management. 15(3). 1 indexed citations
5.
Khan, Samir & Johan Ugander. (2024). Doubly robust and heteroscedasticity-aware sample trimming for causal inference. Biometrika. 112(2).
6.
Khan, Samir, Takehisa Yairi, Seiji Tsutsumi, & Shinichi Nakasuka. (2024). A review of physics-based learning for system health management. Annual Reviews in Control. 57. 100932–100932. 9 indexed citations
7.
Khan, Samir & Johan Ugander. (2023). Adaptive normalization for IPW estimation. SHILAP Revista de lepidopterología. 11(1). 2 indexed citations
8.
Tsutsumi, Seiji, et al.. (2023). Multifidelity Framework for Small Satellite Thermal Analysis. Journal of Spacecraft and Rockets. 61(1). 61–71. 1 indexed citations
9.
Galbraith, W., Samir Khan, James E. Gardner, & Byron J. Schneider. (2022). Myocardial infarction following held antiplatelet therapy for lumbar radiofrequency neurotomy: A letter to the editor. Interventional Pain Medicine. 2(1). 100171–100171. 1 indexed citations
10.
Khan, Samir, Takehisa Yairi, Shinichi Nakasuka, & Seiji Tsutsumi. (2022). Reinforcement Learning-based Anomaly Detection for PHM applications. 2022 IEEE Aerospace Conference (AERO). 4. 1–7.
11.
Khan, Samir, et al.. (2022). ID:15833 Paracervical Muscle Edema After the Use of High-Percussion Massage Gun. Neuromodulation Technology at the Neural Interface. 25(4). S56–S56. 1 indexed citations
12.
Tsutsumi, Seiji, et al.. (2021). Towards a Digital Twin Enabled Multifidelity Framework for Small Satellites. PHM Society European Conference. 6(1). 10–10. 3 indexed citations
13.
Khan, Samir, Michael Farnsworth, Richard McWilliam, & John Ahmet Erkoyuncu. (2020). On the requirements of digital twin-driven autonomous maintenance. Annual Reviews in Control. 50. 13–28. 72 indexed citations
14.
Khan, Samir & Takehisa Yairi. (2018). A review on the application of deep learning in system health management. Mechanical Systems and Signal Processing. 107. 241–265. 842 indexed citations breakdown →
15.
Khan, Samir & Takehisa Yairi. (2017). Perspectives on using deep learning for system health management. 1(1). 1 indexed citations
16.
Sedighi, Tabassom, Peter Foote, & Samir Khan. (2015). Intermittent fault detection on an experimental aircraft fuel rig: Reduce the No Fault Found rate. 110–115. 6 indexed citations
17.
Jennions, Ian, et al.. (2015). No Fault Found: The Search for the Root Cause. SAE International eBooks. 8 indexed citations
18.
Khan, Samir. (2015). Research study from industry-university collaboration on “No Fault Found” events. Journal of Quality in Maintenance Engineering. 21(2). 186–206. 7 indexed citations
19.
Khan, Samir, et al.. (2013). No Fault Found events in maintenance engineering Part 2: Root causes, technical developments and future research. Reliability Engineering & System Safety. 123. 196–208. 36 indexed citations
20.
Khan, Samir, et al.. (2013). No Fault Found events in maintenance engineering Part 1: Current trends, implications and organizational practices. Reliability Engineering & System Safety. 123. 183–195. 52 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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