Sérgio Campos

4.1k total citations
57 papers, 440 citations indexed

About

Sérgio Campos is a scholar working on Computational Theory and Mathematics, Computer Networks and Communications and Hardware and Architecture. According to data from OpenAlex, Sérgio Campos has authored 57 papers receiving a total of 440 indexed citations (citations by other indexed papers that have themselves been cited), including 21 papers in Computational Theory and Mathematics, 16 papers in Computer Networks and Communications and 14 papers in Hardware and Architecture. Recurrent topics in Sérgio Campos's work include Formal Methods in Verification (21 papers), Peer-to-Peer Network Technologies (13 papers) and Caching and Content Delivery (13 papers). Sérgio Campos is often cited by papers focused on Formal Methods in Verification (21 papers), Peer-to-Peer Network Technologies (13 papers) and Caching and Content Delivery (13 papers). Sérgio Campos collaborates with scholars based in Brazil, United States and Argentina. Sérgio Campos's co-authors include Jussara M. Almeida, Marius Minea, Edmund M. Clarke, E. M. Clarke, L.M. Fonseca, W. Marrero, Ítalo Cunha, Ronnie Alves, Alex Borges Vieira and Marcelo de Almeida Maia and has published in prestigious journals such as Journal of Dairy Science, BMC Genomics and Theriogenology.

In The Last Decade

Sérgio Campos

54 papers receiving 408 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sérgio Campos Brazil 14 118 110 90 64 63 57 440
John R. Rose United States 14 70 0.6× 95 0.9× 137 1.5× 32 0.5× 178 2.8× 54 513
Timo Mantere Finland 9 38 0.3× 24 0.2× 35 0.4× 47 0.7× 70 1.1× 28 501
V. Valli Kumari India 12 198 1.7× 40 0.4× 25 0.3× 19 0.3× 190 3.0× 97 524
S.C. Kothari United States 13 110 0.9× 12 0.1× 113 1.3× 61 1.0× 180 2.9× 44 527
Tran van Trung Germany 16 73 0.6× 107 1.0× 110 1.2× 61 1.0× 473 7.5× 78 893
David Harle United Kingdom 16 343 2.9× 24 0.2× 23 0.3× 16 0.3× 122 1.9× 73 707
Henning Christiansen Denmark 11 47 0.4× 29 0.3× 42 0.5× 24 0.4× 162 2.6× 65 367
Mahfooz Alam India 17 286 2.4× 21 0.2× 121 1.3× 15 0.2× 77 1.2× 78 962
Steven S. Lumetta United States 15 427 3.6× 15 0.1× 36 0.4× 20 0.3× 36 0.6× 58 709
Behrouz Zolfaghari United States 12 133 1.1× 21 0.2× 50 0.6× 12 0.2× 100 1.6× 42 460

Countries citing papers authored by Sérgio Campos

Since Specialization
Citations

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

Fields of papers citing papers by Sérgio Campos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sérgio Campos

This figure shows the co-authorship network connecting the top 25 collaborators of Sérgio Campos. A scholar is included among the top collaborators of Sérgio Campos 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 Sérgio Campos. Sérgio Campos 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.
Shiratsuchi, Luciano Shozo, et al.. (2025). A neural network approach employed to classify soybean plants using multi-sensor images. Precision Agriculture. 26(2).
2.
Setiyono, Tri, et al.. (2025). Identification of soybean planting gaps using machine learning. Smart Agricultural Technology. 10. 100779–100779. 5 indexed citations
3.
Assis, Débora Cristina Sampaio de, et al.. (2023). Determination of the lactose content in low-lactose milk using Fourier-transform infrared spectroscopy (FTIR) and convolutional neural network. Heliyon. 9(1). e12898–e12898. 14 indexed citations
4.
Gomes, Giovanni Freitas, et al.. (2023). Stochastic formal model of PI3K/mTOR pathway in Alzheimer's disease for drug repurposing: An evaluation of rapamycin, LY294002, and NVP-BEZ235. Science of Computer Programming. 232. 103028–103028. 1 indexed citations
5.
Campos, Sérgio, et al.. (2022). A machine learning proposal method to detect milk tainted with cheese whey. Journal of Dairy Science. 105(12). 9496–9508. 17 indexed citations
6.
Riesco, Daniel Eduardo, et al.. (2020). In Silico Laboratory Experiments Using Statistical Model Checking: A New Model of the Palytoxin-Induced Pump Channel as Case Study. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 18(6). 2816–2822. 3 indexed citations
7.
Alves, Ronnie, et al.. (2019). On the utilization of deep and ensemble learning to detect milk adulteration. BioData Mining. 12(1). 13–13. 62 indexed citations
8.
Campos, Sérgio, et al.. (2018). Temporal Verification of Real-Time Systems. IEICE Transactions on Information and Systems. 78(7). 796–801. 1 indexed citations
9.
Cunha, Ítalo, et al.. (2017). AERO: Adaptive Emergency Request Optimization in CDN-P2P Live Streaming. pp. 1–7. 3 indexed citations
10.
Almeida-Souza, Hebréia O., Paulo Roberto Gomes Pereira, Maura V. Prates, et al.. (2016). Computer aided identification of a Hevein-like antimicrobial peptide of bell pepper leaves for biotechnological use. BMC Genomics. 17(S12). 999–999. 16 indexed citations
11.
Pereira, Paulo Roberto Gomes, et al.. (2016). Differential abundances of four forms of Binder of SPerm 1 in the seminal plasma of Bos taurus indicus bulls with different patterns of semen freezability. Theriogenology. 86(3). 766–777.e2. 18 indexed citations
12.
Loureiro, Antônio A. F., et al.. (2015). A Probabilistic Model Checking Analysis of Vehicular Ad-Hoc Networks. 1–7. 3 indexed citations
13.
Cruz, Jáder Santos, et al.. (2013). Probabilistic Model Checking Analysis of Palytoxin Effects on Cell Energy Reactions of the Na+/K+-ATPase. IEEE/ACM Transactions on Computational Biology and Bioinformatics. 10(6). 1530–1541. 1 indexed citations
14.
Campos, Sérgio, et al.. (2012). Verification of P2P live streaming systems using symmetry-based semiautomatic abstractions. 697. 343–349. 2 indexed citations
15.
Abreu, Vinícius Augusto Carvalho de, Paulo Mendonça, Vinícius M. Alves, et al.. (2011). PRODIS: a proteomics data management system with support to experiment tracking. BMC Genomics. 12(Suppl 4). S15–S15. 4 indexed citations
16.
Lana–Peixoto, Marco Aurélio, et al.. (2011). NMO-DBr: the Brazilian Neuromyelitis Optica Database System. Arquivos de Neuro-Psiquiatria. 69(4). 687–692. 5 indexed citations
17.
Vieira, Alex Borges, et al.. (2004). EasyPres: An Easy-to-Use Tool for Creating Synchronized Multimedia Presentations.. EdMedia: World Conference on Educational Media and Technology. 2004(1). 949–956. 1 indexed citations
18.
Campos, Sérgio, et al.. (2003). Guaranteeing Fault Tolerance through Scheduling on a CAN Bus. 43–50. 1 indexed citations
19.
Pereira, Adriano C. M., et al.. (2003). Extending UML to Specify and Verify E-commerce Systems.. Software Engineering and Knowledge Engineering. 306–313. 1 indexed citations
20.
Campos, Sérgio & Edmund M. Clarke. (2001). The Verus language: representing time efficiently with BDDs. Theoretical Computer Science. 253(1). 95–118. 5 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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