Barbara Pes

1.1k total citations
47 papers, 563 citations indexed

About

Barbara Pes is a scholar working on Artificial Intelligence, Molecular Biology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Barbara Pes has authored 47 papers receiving a total of 563 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 15 papers in Molecular Biology and 12 papers in Computer Vision and Pattern Recognition. Recurrent topics in Barbara Pes's work include Gene expression and cancer classification (8 papers), Scientific Computing and Data Management (7 papers) and Machine Learning in Bioinformatics (6 papers). Barbara Pes is often cited by papers focused on Gene expression and cancer classification (8 papers), Scientific Computing and Data Management (7 papers) and Machine Learning in Bioinformatics (6 papers). Barbara Pes collaborates with scholars based in Italy, Brazil and Greece. Barbara Pes's co-authors include Nicoletta Dessì, Andrea Bosin, Andrea Loddo, Daniele Riboni, Maurizio Atzori, Marco Manca, Letizia Tanca, Mariagrazia Fugini, Cecilia Di Ruberto and Georgia Koutrika and has published in prestigious journals such as Scientific Reports, Expert Systems with Applications and IEEE Access.

In The Last Decade

Barbara Pes

40 papers receiving 534 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Barbara Pes Italy 12 270 154 125 77 51 47 563
Andrea Bommert Germany 4 251 0.9× 121 0.8× 97 0.8× 51 0.7× 31 0.6× 8 583
Vaibhav Rajan Singapore 15 270 1.0× 209 1.4× 71 0.6× 109 1.4× 57 1.1× 62 741
Pablo Bermejo Spain 10 336 1.2× 78 0.5× 136 1.1× 93 1.2× 46 0.9× 26 591
Rasmita Dash India 12 251 0.9× 108 0.7× 73 0.6× 43 0.6× 27 0.5× 45 430
Fazel Famili Canada 11 308 1.1× 143 0.9× 104 0.8× 76 1.0× 20 0.4× 23 555
Jun Shu China 12 205 0.8× 95 0.6× 104 0.8× 21 0.3× 74 1.5× 35 540
K. A. Abdul Nazeer India 9 256 0.9× 73 0.5× 156 1.2× 105 1.4× 32 0.6× 32 492
Kilian Stoffel Switzerland 8 322 1.2× 90 0.6× 126 1.0× 132 1.7× 75 1.5× 29 652
Edmon Begoli United States 13 282 1.0× 82 0.5× 46 0.4× 107 1.4× 105 2.1× 38 654
Andri Mirzal Malaysia 7 243 0.9× 235 1.5× 178 1.4× 50 0.6× 17 0.3× 23 653

Countries citing papers authored by Barbara Pes

Since Specialization
Citations

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

Fields of papers citing papers by Barbara Pes

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Barbara Pes

This figure shows the co-authorship network connecting the top 25 collaborators of Barbara Pes. A scholar is included among the top collaborators of Barbara Pes 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 Barbara Pes. Barbara Pes 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.
Ruberto, Cecilia Di, et al.. (2025). CRDet: An Artificial Intelligence-Based Framework for Automated Cheese Ripeness Assessment from Digital Images. IEEE/CAA Journal of Automatica Sinica. 12(10). 2082–2102.
2.
Loddo, Andrea, et al.. (2024). Insights into radiomics: impact of feature selection and classification. Multimedia Tools and Applications. 84(26). 31695–31721. 11 indexed citations
3.
Loddo, Andrea, et al.. (2024). An Anomaly Detection Approach to Determine Optimal Cutting Time in Cheese Formation. Information. 15(6). 360–360. 1 indexed citations
4.
Pes, Barbara, et al.. (2023). An Evaluation of Feature Selection Robustness on Class Noisy Data. Information. 14(8). 438–438. 4 indexed citations
5.
Orrù, Sandro, Barbara Pes, Gianfranco Fancello, et al.. (2023). Biomarker dynamics affecting neoadjuvant therapy response and outcome of HER2-positive breast cancer subtype. Scientific Reports. 13(1). 12869–12869. 2 indexed citations
6.
Manca, Marco, et al.. (2022). Towards Context-aware Power Forecasting in Smart-homes. Procedia Computer Science. 198. 243–248. 2 indexed citations
7.
Pes, Barbara. (2021). Special Issue on Emerging Trends and Challenges in Supervised Learning Tasks. Information. 12(11). 481–481. 1 indexed citations
8.
Pes, Barbara. (2021). Learning from High-Dimensional and Class-Imbalanced Datasets Using Random Forests. Information. 12(8). 286–286. 29 indexed citations
9.
Atzori, Maurizio, Georgia Koutrika, Barbara Pes, & Letizia Tanca. (2020). Special issue on “Data Exploration in the Web 3.0 Age”. Future Generation Computer Systems. 112. 1177–1179. 10 indexed citations
10.
Atzori, Maurizio & Barbara Pes. (2018). Summary Report for the Data Exploration in the Web 3.0 Age (DEW) Track. UNICA IRIS Institutional Research Information System (University of Cagliari). 24. 139–141.
11.
Dessì, Nicoletta, et al.. (2015). An Evolutionary Approach for Balancing Effectiveness and Representation Level in Gene Selection. Journal of Information Technology Research. 8(2). 16–33. 2 indexed citations
12.
Dessì, Nicoletta, et al.. (2015). COWB: A cloud-based framework supporting collaborative knowledge management within biomedical communities. Future Generation Computer Systems. 54. 399–408. 5 indexed citations
13.
Dessì, Nicoletta, et al.. (2015). Towards Ontology-Enabled BioContexts for Bioinformatics Research. UNICA IRIS Institutional Research Information System (University of Cagliari). 2006. 236–238.
14.
Costa, João C. Diniz da, et al.. (2013). Nanoelectronic SET-based core for Network-on-chip architectures. TechConnect Briefs. 2(2013). 29–32.
15.
Dessì, Nicoletta, et al.. (2013). Assessing similarity of feature selection techniques in high-dimensional domains. Pattern Recognition Letters. 34(12). 1446–1453. 20 indexed citations
16.
Dessì, Nicoletta, et al.. (2013). A Comparative Analysis of Biomarker Selection Techniques. BioMed Research International. 2013. 1–10. 31 indexed citations
17.
Dessì, Nicoletta, et al.. (2012). Pre-filtering Features in Random Forests for Microarray Data Classification. UNICA IRIS Institutional Research Information System (University of Cagliari). 60–67. 1 indexed citations
18.
Dessì, Nicoletta, et al.. (2010). Tuning Evolutionary Algorithms in High Dimensional Classification Problems. UNICA IRIS Institutional Research Information System (University of Cagliari). 142–149. 1 indexed citations
19.
Dessì, Nicoletta & Barbara Pes. (2009). Towards Scientific Dataspaces. UNICA IRIS Institutional Research Information System (University of Cagliari). 575–578. 2 indexed citations
20.
Dessì, Nicoletta & Barbara Pes. (2009). An Evolutionary Method for Combining Different Feature Selection Criteria in Microarray Data Classification. UNICA IRIS Institutional Research Information System (University of Cagliari). 2009. 1–10. 13 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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