Philippe Leray

2.0k total citations
166 papers, 924 citations indexed

About

Philippe Leray is a scholar working on Electrical and Electronic Engineering, Surfaces, Coatings and Films and Artificial Intelligence. According to data from OpenAlex, Philippe Leray has authored 166 papers receiving a total of 924 indexed citations (citations by other indexed papers that have themselves been cited), including 113 papers in Electrical and Electronic Engineering, 63 papers in Surfaces, Coatings and Films and 27 papers in Artificial Intelligence. Recurrent topics in Philippe Leray's work include Advancements in Photolithography Techniques (93 papers), Integrated Circuits and Semiconductor Failure Analysis (65 papers) and Optical Coatings and Gratings (34 papers). Philippe Leray is often cited by papers focused on Advancements in Photolithography Techniques (93 papers), Integrated Circuits and Semiconductor Failure Analysis (65 papers) and Optical Coatings and Gratings (34 papers). Philippe Leray collaborates with scholars based in Belgium, France and Netherlands. Philippe Leray's co-authors include Patrick Gallinari, Olivier François, Christine Sinoquet, Raphaël Mourad, Sandip Halder, Bappaditya Dey, Magdy Bayoumi, Koen D’havé, Stijn Meganck and Gian F. Lorusso and has published in prestigious journals such as PLoS ONE, BMC Bioinformatics and Journal of Medical Internet Research.

In The Last Decade

Philippe Leray

141 papers receiving 837 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Philippe Leray Belgium 16 417 230 177 139 91 166 924
Pan United States 13 147 0.4× 91 0.4× 28 0.2× 60 0.4× 48 0.5× 147 646
Anita Raja United States 18 466 1.1× 235 1.0× 31 0.2× 128 0.9× 22 0.2× 106 940
Chenxi Lin United States 18 736 1.8× 235 1.0× 92 0.5× 668 4.8× 68 0.7× 61 1.8k
Shi Chen China 19 325 0.8× 199 0.9× 8 0.0× 126 0.9× 41 0.5× 72 1.0k
Bhavya Kailkhura United States 19 243 0.6× 587 2.6× 9 0.1× 80 0.6× 22 0.2× 73 1.3k
Olivier Teytaud France 19 93 0.2× 843 3.7× 22 0.1× 28 0.2× 24 0.3× 101 1.2k
Youssef Drissi Belgium 8 135 0.3× 501 2.2× 12 0.1× 27 0.2× 26 0.3× 27 831
Abdul Basit Pakistan 20 324 0.8× 166 0.7× 11 0.1× 123 0.9× 10 0.1× 96 1.4k
Nadine Le Fort-Piat France 14 111 0.3× 188 0.8× 16 0.1× 148 1.1× 31 0.3× 37 703

Countries citing papers authored by Philippe Leray

Since Specialization
Citations

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

Fields of papers citing papers by Philippe Leray

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Philippe Leray

This figure shows the co-authorship network connecting the top 25 collaborators of Philippe Leray. A scholar is included among the top collaborators of Philippe Leray 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 Philippe Leray. Philippe Leray 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.
Chen, Ying-Lin, Bappaditya Dey, Víctor Blanco, et al.. (2024). Exploring Machine Learning for Semiconductor Process Optimization: A Systematic Review. IEEE Transactions on Artificial Intelligence. 5(12). 5969–5989. 8 indexed citations
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Chen, Ying-Lin, et al.. (2024). Towards improved semiconductor defect inspection for high-NA EUVL based on SEMI-SuperYOLO-NAS. Ghent University Academic Bibliography (Ghent University). 30–30. 1 indexed citations
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Amor, Nahla Ben, et al.. (2024). Approximate inference on optimized quantum Bayesian networks. International Journal of Approximate Reasoning. 175. 109307–109307. 2 indexed citations
9.
Hermans, Yannick, Chen Wu, Filip Schleicher, et al.. (2023). BEOL N2: M2 through SAxP process from MP21 to MP26: 193i SAQP vs EUV SADP. 57–57. 1 indexed citations
10.
Poortere, E. P. De, et al.. (2023). Voltage contrast determination of design rules at the limits of EUV single patterning. Journal of Micro/Nanopatterning Materials and Metrology. 22(4). 2 indexed citations
11.
Dey, Bappaditya, et al.. (2022). Deep learning-based defect classification and detection in SEM images. arXiv (Cornell University). 83–83. 16 indexed citations
12.
Dey, Bappaditya, et al.. (2022). Deep learning based defect classification and detection in SEM images: a mask R-CNN approach. Lirias (KU Leuven). 43–43. 9 indexed citations
13.
Dey, Bappaditya, Sandip Halder, Kasem Khalil, et al.. (2021). SEM image denoising with unsupervised machine learning for better defect inspection and metrology. 33–33. 16 indexed citations
14.
Asvatourian, Vahé, Philippe Leray, Stefan Michiels, & Émilie Lanoy. (2020). Integrating expert’s knowledge constraint of time dependent exposures in structure learning for Bayesian networks. Artificial Intelligence in Medicine. 107. 101874–101874. 10 indexed citations
15.
Mourad, Raphaël, Christine Sinoquet, & Philippe Leray. (2011). Probabilistic graphical models for genetic association studies. Briefings in Bioinformatics. 13(1). 20–33. 16 indexed citations
16.
Mourad, Raphaël, Christine Sinoquet, & Philippe Leray. (2011). A hierarchical Bayesian network approach for linkage disequilibrium modeling and data-dimensionality reduction prior to genome-wide association studies. BMC Bioinformatics. 12(1). 16–16. 39 indexed citations
17.
Leray, Philippe, et al.. (2008). A Bayesian Network Model for Discovering Handwriting Strategies of Primary School Children. 1 indexed citations
18.
Meganck, Stijn, Sam Maes, Philippe Leray, & Bernard Manderick. (2006). Learning Semi-Markovian Causal Models using Experiments. VUBIR (Vrije Universiteit Brussel). 18(1). 195–206. 3 indexed citations
19.
François, Olivier & Philippe Leray. (2006). Learning the Tree Augmented Naive Bayes Classifier from incomplete datasets.. 91–98. 9 indexed citations
20.
Witters, Liesbeth, et al.. (2004). Requirements on CD and overlay for 200 GHz QSA SiGe:C HBTs. 333–336. 1 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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