José Machado

2.4k total citations
191 papers, 992 citations indexed

About

José Machado is a scholar working on Industrial and Manufacturing Engineering, Computational Theory and Mathematics and Biomedical Engineering. According to data from OpenAlex, José Machado has authored 191 papers receiving a total of 992 indexed citations (citations by other indexed papers that have themselves been cited), including 44 papers in Industrial and Manufacturing Engineering, 35 papers in Computational Theory and Mathematics and 25 papers in Biomedical Engineering. Recurrent topics in José Machado's work include Formal Methods in Verification (26 papers), Digital Transformation in Industry (16 papers) and Flexible and Reconfigurable Manufacturing Systems (16 papers). José Machado is often cited by papers focused on Formal Methods in Verification (26 papers), Digital Transformation in Industry (16 papers) and Flexible and Reconfigurable Manufacturing Systems (16 papers). José Machado collaborates with scholars based in Portugal, Poland and India. José Machado's co-authors include Leonilde Varela, Filomena Soares, Vı́tor Carvalho, Luís Mendes, Vijaya Kumar Manupati, José Creissac Campos, Eurico Seabra, Justyna Trojanowska, Goran D. Putnik and Katarzyna Antosz and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Transactions on Industrial Electronics.

In The Last Decade

José Machado

162 papers receiving 937 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
José Machado Portugal 16 314 116 108 106 95 191 992
Anna Syberfeldt Sweden 20 454 1.4× 111 1.0× 63 0.6× 119 1.1× 72 0.8× 80 1.2k
Emanuele Carpanzano Italy 19 547 1.7× 149 1.3× 146 1.4× 217 2.0× 45 0.5× 70 943
Leon Urbas Germany 19 607 1.9× 84 0.7× 54 0.5× 288 2.7× 177 1.9× 188 1.4k
Zuhua Jiang China 21 604 1.9× 33 0.3× 175 1.6× 60 0.6× 96 1.0× 110 1.4k
Dan Trietsch United States 19 719 2.3× 60 0.5× 27 0.3× 92 0.9× 203 2.1× 51 1.4k
Saeed Maghsoodloo United States 19 184 0.6× 63 0.5× 159 1.5× 38 0.4× 32 0.3× 59 960
Brian K. Thorn United States 11 234 0.7× 96 0.8× 450 4.2× 362 3.4× 64 0.7× 28 1.8k
Arkadiusz Gola Poland 19 582 1.9× 17 0.1× 242 2.2× 84 0.8× 109 1.1× 106 1.1k
Manbir Sodhi United States 17 270 0.9× 32 0.3× 160 1.5× 54 0.5× 64 0.7× 50 1.1k
Stephen C.-Y. Lu United States 20 1.1k 3.5× 72 0.6× 458 4.2× 108 1.0× 138 1.5× 101 2.1k

Countries citing papers authored by José Machado

Since Specialization
Citations

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

Fields of papers citing papers by José Machado

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of José Machado

This figure shows the co-authorship network connecting the top 25 collaborators of José Machado. A scholar is included among the top collaborators of José Machado 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 José Machado. José Machado 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.
Pereira, Filipe, et al.. (2025). Yarn quality analysis by using computer vision and deep learning techniques. Textile Research Journal. 96(3-4). 240–265.
2.
Pereira, Filipe, et al.. (2025). Integration of Deep Learning Vision Systems in Collaborative Robotics for Real-Time Applications. Applied Sciences. 15(3). 1336–1336. 1 indexed citations
3.
Pereira, Filipe, et al.. (2024). OPC-UA in interoperability – a performance comparative testing. IFAC-PapersOnLine. 58(8). 240–245. 2 indexed citations
5.
Pereira, Filipe, et al.. (2024). Development of an Automated Wooden Handle Packaging System with Integrated Counting Technology. Machines. 12(2). 122–122. 2 indexed citations
6.
Prokopenko, Olha, et al.. (2024). Development of Blockchain Technology in Financial Accounting. Computation. 12(12). 250–250. 2 indexed citations
7.
Machado, José, et al.. (2023). Application of Carbide Cutting Inserts as Indenters for Surface Plastic Deformation. Applied Sciences. 13(6). 3741–3741.
8.
Pereira, Filipe, Alexandre José Macêdo, Filomena Soares, et al.. (2023). Intelligent Computer Vision System for Analysis and Characterization of Yarn Quality. Electronics. 12(1). 236–236. 6 indexed citations
9.
Oliveira, Paulo Moura, et al.. (2023). Temperature Control Laboratory (TCLab): Demonstration of Use in Portugal. 13–14.
10.
Rocha, Daniel, et al.. (2023). Using Object Detection Technology to Identify Defects in Clothing for Blind People. Sensors. 23(9). 4381–4381. 6 indexed citations
11.
Varela, Leonilde, et al.. (2023). Global Resources Management: A Systematic Review and Framework Proposal for Collaborative Management of CPPS. Applied Sciences. 13(2). 750–750. 2 indexed citations
12.
Antosz, Katarzyna, Małgorzata Jasiulewicz–Kaczmarek, Robert Waszkowski, & José Machado. (2022). Application of Lean Six Sigma for sustainable maintenance: case study. IFAC-PapersOnLine. 55(19). 181–186. 14 indexed citations
13.
Silva, Luís, V.H. Carneiro, A. Manuela Gonçalves, et al.. (2022). A Novel Route to Optimize Placement Equipment Kinematics by Coupling Capacitive Accelerometers. Sensors. 22(9). 3423–3423. 1 indexed citations
14.
Kandeva, M. K., et al.. (2019). Simple Technique and Device for Slurries Viscosity Measurement. Journal of Environmental Protection and Ecology. 20(2). 761–772. 1 indexed citations
15.
Manupati, Vijaya Kumar, et al.. (2018). AN ANALYSIS OF THE IMPACT OF UTAUT PREDICTORS ON THE INTENTION AND USAGE OF ELECTRONIC HEALTH RECORDS AND TELEMEDICINE FROM THE PERSPECTIVE OF CLINICAL STAFFS. International Journal of Mechatronics and Applied Mechanics. 1(4). 4 indexed citations
16.
Leão, Celina P., José Machado, Eurico Seabra, José Creissac Campos, & Filomena Soares. (2017). Safe Controllers Design for Industrial Automation Systems. Portuguese National Funding Agency for Science, Research and Technology (RCAAP Project by FCT). 7 indexed citations
17.
Torres, Elizabeth B., et al.. (2017). How doing a dynamical analysis of gait movement may provide information about Autism. Bulletin of the American Physical Society. 2017. 1 indexed citations
18.
Soares, Filomena, Celina P. Leão, José Machado, & Vı́tor Carvalho. (2015). Experiences in Automation and Control in Engineering Education with Real-world Based Educational Kits. SHILAP Revista de lepidopterología. 3 indexed citations
19.
Campos, José Creissac & José Machado. (2011). Supporting requirements formulation in software formal verification. Biblioteca Digital da Memória Científica do INPE (National Institute for Space Research).
20.
Machado, José, et al.. (2004). MODEL OF MECHANISM BEHAVIOR FOR VERIFICATION OF PLC PROGRAMS. RepositóriUM (Universidade do Minho). 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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