Catherine da Cunha

1.0k total citations
38 papers, 655 citations indexed

About

Catherine da Cunha is a scholar working on Management of Technology and Innovation, Industrial and Manufacturing Engineering and Mechanical Engineering. According to data from OpenAlex, Catherine da Cunha has authored 38 papers receiving a total of 655 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Management of Technology and Innovation, 17 papers in Industrial and Manufacturing Engineering and 11 papers in Mechanical Engineering. Recurrent topics in Catherine da Cunha's work include Product Development and Customization (15 papers), Manufacturing Process and Optimization (10 papers) and Design Education and Practice (9 papers). Catherine da Cunha is often cited by papers focused on Product Development and Customization (15 papers), Manufacturing Process and Optimization (10 papers) and Design Education and Practice (9 papers). Catherine da Cunha collaborates with scholars based in France, Canada and United States. Catherine da Cunha's co-authors include Alain Bernard, Bruno Agard, Andrew Kusiak, Mathieu Ritou, Farouk Belkadi, Joanna Daaboul, Florent Laroche, Benoît Furet, Khaled Medini and Émilie Poirson and has published in prestigious journals such as Expert Systems with Applications, International Journal of Production Research and CIRP Annals.

In The Last Decade

Catherine da Cunha

34 papers receiving 635 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Catherine da Cunha France 14 284 236 121 99 96 38 655
Nanua Singh United States 15 295 1.0× 225 1.0× 140 1.2× 107 1.1× 101 1.1× 39 854
Julien Le Duigou France 17 382 1.3× 159 0.7× 181 1.5× 114 1.2× 80 0.8× 54 691
Josip Stjepandić Italy 15 341 1.2× 143 0.6× 95 0.8× 78 0.8× 131 1.4× 45 716
Peter Burggräf Germany 15 438 1.5× 129 0.5× 88 0.7× 93 0.9× 109 1.1× 137 813
Kouroush Jenab United States 17 151 0.5× 141 0.6× 52 0.4× 111 1.1× 130 1.4× 111 720
Marko Mladineo Croatia 16 520 1.8× 104 0.4× 59 0.5× 114 1.2× 135 1.4× 52 788
Maik Maurer Germany 10 297 1.0× 574 2.4× 379 3.1× 82 0.8× 66 0.7× 57 783
Venkat Allada United States 14 315 1.1× 226 1.0× 195 1.6× 117 1.2× 96 1.0× 44 607
David S. Cochran United States 15 506 1.8× 311 1.3× 126 1.0× 111 1.1× 260 2.7× 56 865

Countries citing papers authored by Catherine da Cunha

Since Specialization
Citations

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

Fields of papers citing papers by Catherine da Cunha

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Catherine da Cunha. 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 Catherine da Cunha. The network helps show where Catherine da Cunha may publish in the future.

Co-authorship network of co-authors of Catherine da Cunha

This figure shows the co-authorship network connecting the top 25 collaborators of Catherine da Cunha. A scholar is included among the top collaborators of Catherine da Cunha 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 Catherine da Cunha. Catherine da Cunha 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.
2.
Cunha, Catherine da, et al.. (2025). Validation of multidimensional performance assessment models using hierarchical clustering. Expert Systems with Applications. 290. 128446–128446.
3.
Cunha, Catherine da, et al.. (2023). A Multi-Stage Model for Sustainable Scheduling in Hybrid Flexible Flow Shop. SPIRE - Sciences Po Institutional REpository. 758–763.
4.
Cunha, Catherine da, et al.. (2022). Production Planning and Control for Sustainable Management Systems. IFAC-PapersOnLine. 55(10). 1968–1973. 1 indexed citations
5.
Cunha, Catherine da, et al.. (2021). Designing the Digital Twins of Reconfigurable Manufacturing Systems: application on a smart factory. IFAC-PapersOnLine. 54(1). 874–879. 15 indexed citations
6.
Cunha, Catherine da, et al.. (2021). Literature review and discussion on collaborative decision making approaches in Industry 4.0. FME Transaction. 49(4). 817–826. 5 indexed citations
7.
Cunha, Catherine da, et al.. (2021). A Semantic Model Framework for the Cyber‐Physical Production System in the Systems Engineering Perspective. Insight. 24(4). 16–17. 1 indexed citations
8.
Cunha, Catherine da, et al.. (2020). Lessons learned from the use of various formats for disseminating and communicating climate knowledge. Utrecht University Repository (Utrecht University). 1 indexed citations
9.
Ritou, Mathieu, et al.. (2020). Contextual classification for smart machining based on unsupervised machine learning by Gaussian mixture model. International Journal of Computer Integrated Manufacturing. 33(10-11). 1042–1054. 12 indexed citations
10.
Belkadi, Farouk, et al.. (2020). A knowledge-based Digital Shadow for machining industry in a Digital Twin perspective. Journal of Manufacturing Systems. 58. 168–179. 116 indexed citations
11.
Cunha, Catherine da, et al.. (2019). Comparison of K-means and GMM methods for contextual clustering in HSM. Procedia Manufacturing. 28. 154–159. 32 indexed citations
12.
Poirson, Émilie & Catherine da Cunha. (2018). A recommender approach based on customer emotions. Expert Systems with Applications. 122. 281–288. 19 indexed citations
13.
Gupta, Ravi Kumar, et al.. (2017). Gathering, evaluating and managing customer feedback during aircraft production. Computers & Industrial Engineering. 115. 559–572. 19 indexed citations
14.
Daaboul, Joanna, et al.. (2015). Differentiation and customer decoupling points: An integrated design approach for mass customization. Concurrent Engineering. 23(4). 284–295. 12 indexed citations
15.
Medini, Khaled, Catherine da Cunha, & Alain Bernard. (2014). Tailoring performance evaluation to specific industrial contexts – application to sustainable mass customisation enterprises. International Journal of Production Research. 53(8). 2439–2456. 23 indexed citations
16.
Daaboul, Joanna, Pierre Castagna, Catherine da Cunha, & Alain Bernard. (2014). Value network modelling and simulation for strategic analysis: a discrete event simulation approach. International Journal of Production Research. 52(17). 5002–5020. 23 indexed citations
17.
Daaboul, Joanna, Catherine da Cunha, Alain Bernard, & Florent Laroche. (2011). Design for mass customization: Product variety vs. process variety. CIRP Annals. 60(1). 169–174. 56 indexed citations
18.
19.
Agard, Bruno, et al.. (2008). Composition of module stock for final assembly using an enhanced genetic algorithm. International Journal of Production Research. 47(20). 5829–5842. 6 indexed citations
20.
Cunha, Catherine da, Bruno Agard, & Andrew Kusiak. (2007). Design for Cost: Module-Based Mass Customization. IEEE Transactions on Automation Science and Engineering. 4(3). 350–359. 57 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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