Samuel Bigot

1.5k total citations
65 papers, 1.1k citations indexed

About

Samuel Bigot is a scholar working on Mechanical Engineering, Biomedical Engineering and Electrical and Electronic Engineering. According to data from OpenAlex, Samuel Bigot has authored 65 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 38 papers in Mechanical Engineering, 27 papers in Biomedical Engineering and 25 papers in Electrical and Electronic Engineering. Recurrent topics in Samuel Bigot's work include Advanced Machining and Optimization Techniques (19 papers), Advanced machining processes and optimization (18 papers) and Advanced Surface Polishing Techniques (16 papers). Samuel Bigot is often cited by papers focused on Advanced Machining and Optimization Techniques (19 papers), Advanced machining processes and optimization (18 papers) and Advanced Surface Polishing Techniques (16 papers). Samuel Bigot collaborates with scholars based in United Kingdom, France and Germany. Samuel Bigot's co-authors include Stefan Dimov, Duc Truong Pham, Atanas Ivanov, Krastimir Borisov Popov, Franck Lacan, Emmanuel Brousseau, Chao Liu, Carolin Körner, Hanxing Zhu and Yang Jiao and has published in prestigious journals such as Materials Science and Engineering A, Applied Surface Science and Journal of Materials Processing Technology.

In The Last Decade

Samuel Bigot

54 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Samuel Bigot United Kingdom 15 697 440 418 218 213 65 1.1k
Hazim El-Mounayri United States 23 989 1.4× 222 0.5× 262 0.6× 419 1.9× 473 2.2× 80 1.3k
Xiaohong Lü China 20 864 1.2× 447 1.0× 581 1.4× 227 1.0× 104 0.5× 88 1.3k
M. Chandrasekaran India 20 1.0k 1.5× 341 0.8× 582 1.4× 236 1.1× 99 0.5× 100 1.3k
Benoît Furet France 24 1.1k 1.6× 505 1.1× 297 0.7× 470 2.2× 191 0.9× 67 1.8k
Doriana M. D’Addona Italy 23 1.2k 1.7× 528 1.2× 656 1.6× 550 2.5× 118 0.6× 88 1.7k
Vigneashwara Pandiyan Switzerland 21 1.0k 1.5× 420 1.0× 219 0.5× 267 1.2× 245 1.2× 36 1.2k
Dingwen Yu China 23 1.3k 1.8× 585 1.3× 574 1.4× 209 1.0× 78 0.4× 96 1.6k
Oğuzhan Yılmaz Türkiye 17 1.1k 1.5× 269 0.6× 294 0.7× 304 1.4× 504 2.4× 51 1.4k
Zhijun Wu China 21 947 1.4× 379 0.9× 292 0.7× 187 0.9× 54 0.3× 73 1.2k
Y.S. Wong Singapore 20 809 1.2× 351 0.8× 375 0.9× 383 1.8× 252 1.2× 32 1.2k

Countries citing papers authored by Samuel Bigot

Since Specialization
Citations

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

Fields of papers citing papers by Samuel Bigot

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Samuel Bigot

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Bigot. A scholar is included among the top collaborators of Samuel Bigot 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 Samuel Bigot. Samuel Bigot 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.
Bhaduri, Debajyoti, et al.. (2025). A proposed method for enhancing the thermal characteristics of bio-inspired microtextured surfaces for energy sector applications. The International Journal of Advanced Manufacturing Technology.
2.
Soroka, Anthony, et al.. (2024). Developing Rapid Metal AM deformations Prediction using CNN. Procedia CIRP. 126. 567–572.
3.
Green, Anthony R., Wayne Nishio Ayre, Samuel Bigot, Emmanuel Brousseau, & Debajyoti Bhaduri. (2024). Laser Surface Texturing of Bulk Metallic Glass for Orthopaedic Application. ORCA Online Research @Cardiff (Cardiff University). 1–4.
4.
Packianather, Michael, et al.. (2024). A Novel Hybrid Bees Regression Convolutional Neural Network (BA- RCNN) Applied to Porosity Prediction in Selective Laser Melting Parts. ORCA Online Research @Cardiff (Cardiff University). 95–99. 1 indexed citations
5.
Packianather, Michael, et al.. (2023). Optimizing the Parameters of Long Short-Term Memory Networks Using the Bees Algorithm. Applied Sciences. 13(4). 2536–2536. 10 indexed citations
6.
Packianather, Michael, et al.. (2022). Optimization of Convolutional Neural Network Topology and Training Parameters using Bees Algorithm. ORCA Online Research @Cardiff (Cardiff University). 1 indexed citations
7.
Jiao, Yang, Emmanuel Brousseau, Wayne Nishio Ayre, et al.. (2021). In vitro cytocompatibility of a Zr-based metallic glass modified by laser surface texturing for potential implant applications. Applied Surface Science. 547. 149194–149194. 37 indexed citations
8.
Bhaduri, Debajyoti, et al.. (2020). Effects of laser microtextured surfaces in condensation heat transfer. Procedia CIRP. 95. 927–932.
9.
Pernot, Jean-Philippe, et al.. (2020). Machine Learning-Based Reverse Modeling Approach for Rapid Tool Shape Optimization in Die-Sinking Micro Electro Discharge Machining. Journal of Computing and Information Science in Engineering. 20(3). 14 indexed citations
10.
Valera-Medina, Agustín, et al.. (2017). Investigation of boundary layer flashback enhancement in swirl burner using woven wire mesh. ORCA Online Research @Cardiff (Cardiff University). 1 indexed citations
11.
Valera-Medina, Agustín, et al.. (2017). Experimental Study to Enhance Resistance for Boundary Layer Flashback in Swirl Burners Using Microsurfaces. ORCA Online Research @Cardiff (Cardiff University). 10 indexed citations
12.
Pernot, Jean-Philippe, et al.. (2016). Iterative surface warping to shape craters in micro-EDM simulation. Engineering With Computers. 32(3). 517–531. 6 indexed citations
13.
Meydan, T., et al.. (2015). <italic>In Vivo</italic> Monitoring of Orthopaedic Implant Wear Using Amorphous Ribbons. IEEE Transactions on Magnetics. 51(1). 1–3. 1 indexed citations
14.
Bigot, Samuel, et al.. (2013). Micro-EDM Numerical Simulation and Experimental Validation. 55–58. 2 indexed citations
15.
Bigot, Samuel, et al.. (2013). Micro-EDM numerical simulation and experimental Validation. ORCA Online Research @Cardiff (Cardiff University). 55–58. 2 indexed citations
16.
Bigot, Samuel, et al.. (2012). A New Modelling Framework for Die-Sinking Micro EDM. 51–55. 7 indexed citations
17.
Griffiths, C. A., et al.. (2009). Investigation of polymer inserts as prototyping tooling for micro injection moulding. The International Journal of Advanced Manufacturing Technology. 47(1-4). 111–123. 20 indexed citations
18.
Hiller, Karla, Thomas Geßner, Jérôme Gavillet, et al.. (2008). An all-polymer microfluidic system for protein sensing applications with integrated low-cost pumps, surface modification and sealing. ORCA Online Research @Cardiff (Cardiff University). 1–8. 1 indexed citations
19.
Pham, Duc Truong, Atanas Ivanov, Samuel Bigot, Krastimir Borisov Popov, & Stefan Dimov. (2007). A study of micro-electro discharge machining electrode wear. Proceedings of the Institution of Mechanical Engineers Part C Journal of Mechanical Engineering Science. 221(5). 605–612. 29 indexed citations
20.
Vaillant, F., et al.. (1991). Crosstalk and Field to Wire Coupling Problems: The Spice Simulator Approach. 23–28. 2 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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