Cèsar Ferri

5.2k total citations · 2 hit papers
59 papers, 2.7k citations indexed

About

Cèsar Ferri is a scholar working on Artificial Intelligence, Information Systems and Computational Theory and Mathematics. According to data from OpenAlex, Cèsar Ferri has authored 59 papers receiving a total of 2.7k indexed citations (citations by other indexed papers that have themselves been cited), including 40 papers in Artificial Intelligence, 16 papers in Information Systems and 11 papers in Computational Theory and Mathematics. Recurrent topics in Cèsar Ferri's work include Imbalanced Data Classification Techniques (17 papers), Data Mining Algorithms and Applications (14 papers) and Machine Learning and Data Classification (12 papers). Cèsar Ferri is often cited by papers focused on Imbalanced Data Classification Techniques (17 papers), Data Mining Algorithms and Applications (14 papers) and Machine Learning and Data Classification (12 papers). Cèsar Ferri collaborates with scholars based in Spain, United Kingdom and United States. Cèsar Ferri's co-authors include José Hernández‐Orallo, Peter Flach, Marïa José Ramírez-Quintana, Fernando Martínez‐Plumed, Lidia Contreras-Ochando, Nicolas Lachiche, Meelis Kull, Antonio Bella, Niko Beerenwinkel and Vicente Domingo Estruch Fuster and has published in prestigious journals such as Nature, SHILAP Revista de lepidopterología and Expert Systems with Applications.

In The Last Decade

Cèsar Ferri

52 papers receiving 2.6k citations

Hit Papers

Proceedings of the 28th International Conference on Machi... 2008 2026 2014 2020 2011 2008 250 500 750 1000

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Cèsar Ferri Spain 16 1.4k 435 308 181 172 59 2.7k
Richard Maclin United States 13 1.6k 1.1× 519 1.2× 252 0.8× 215 1.2× 132 0.8× 29 2.7k
Bill Fulkerson United States 9 1.2k 0.9× 443 1.0× 283 0.9× 168 0.9× 119 0.7× 15 2.5k
Joaquin Vanschoren Netherlands 24 1.7k 1.2× 341 0.8× 272 0.9× 137 0.8× 187 1.1× 77 2.9k
José Hernández‐Orallo Spain 26 2.0k 1.4× 498 1.1× 402 1.3× 214 1.2× 220 1.3× 110 3.8k
Kian Ming A. Chai Singapore 12 1.7k 1.2× 788 1.8× 215 0.7× 191 1.1× 182 1.1× 20 3.1k
Hsuan-Tien Lin Taiwan 20 1.4k 1.0× 754 1.7× 222 0.7× 189 1.0× 91 0.5× 72 2.6k
David W. Opitz United States 10 1.6k 1.2× 592 1.4× 279 0.9× 234 1.3× 142 0.8× 23 3.1k
Lakhmi C. Jain Australia 29 1.0k 0.7× 353 0.8× 315 1.0× 91 0.5× 191 1.1× 226 2.8k
Kun Zhang United States 23 1.6k 1.2× 652 1.5× 179 0.6× 197 1.1× 281 1.6× 155 2.8k
Alberto Barbado Spain 3 3.0k 2.1× 377 0.9× 317 1.0× 154 0.9× 257 1.5× 5 5.0k

Countries citing papers authored by Cèsar Ferri

Since Specialization
Citations

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

Fields of papers citing papers by Cèsar Ferri

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Cèsar Ferri

This figure shows the co-authorship network connecting the top 25 collaborators of Cèsar Ferri. A scholar is included among the top collaborators of Cèsar Ferri 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 Cèsar Ferri. Cèsar Ferri 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.
Monserrat, C., et al.. (2025). Detection of microfibres in wastewater sludge with deep learning. Results in Engineering. 26. 105454–105454.
2.
Ferri, Cèsar, et al.. (2024). Analysis and discovery of procrastination patterns in a language learning MOOC. Computers & Education. 223. 105154–105154. 1 indexed citations
3.
Ferri, Cèsar, et al.. (2024). Cracking black-box models: Revealing hidden machine learning techniques behind their predictions. Intelligent Data Analysis. 29(1). 28–44. 2 indexed citations
4.
Ghisoni, Francesco, Giovanni Visonà, Roman Kern, et al.. (2023). Explainable AI in Biomedical Research: A Systematic Review and Meta-Analysis. SSRN Electronic Journal. 1 indexed citations
5.
Ghisoni, Francesco, Giovanni Visonà, Roman Kern, et al.. (2023). A historical perspective of biomedical explainable AI research. Patterns. 4(9). 100830–100830. 16 indexed citations
6.
Martínez‐Plumed, Fernando, et al.. (2021). Missing the missing values: The ugly duckling of fairness in machine learning. International Journal of Intelligent Systems. 36(7). 3217–3258. 37 indexed citations
7.
Monserrat, C., et al.. (2020). Learning alternative ways of performing a task. Expert Systems with Applications. 148. 113263–113263. 2 indexed citations
8.
Ferri, Cèsar, et al.. (2019). A dataset of attributes from papers of a machine learning conference. SHILAP Revista de lepidopterología. 24. 103836–103836. 9 indexed citations
9.
Conejero, J. Alberto, et al.. (2017). Zipf's and Benford's laws in Twitter hashtags. 84–93. 3 indexed citations
10.
Martínez‐Plumed, Fernando, Cèsar Ferri, José Hernández‐Orallo, & Marïa José Ramírez-Quintana. (2017). A computational analysis of general intelligence tests for evaluating cognitive development. Cognitive Systems Research. 43. 100–118. 11 indexed citations
11.
Martínez‐Plumed, Fernando, Cèsar Ferri, & Lidia Contreras-Ochando. (2016). Cycling network projects: a decision-making aid approach. RiuNet (Politechnical University of Valencia). 1 indexed citations
12.
Contreras-Ochando, Lidia & Cèsar Ferri. (2016). airVLC: An Application for Visualizing Wind-Sensitive Interpolation of Urban Air Pollution Forecasts. 1296–1299. 6 indexed citations
13.
Contreras-Ochando, Lidia, et al.. (2015). Airvlc: an application for real-time forecasting urban air pollution. International Conference on Machine Learning. 72–79. 8 indexed citations
14.
Gil-Pechuán, Ignacio, et al.. (2013). Strategies in E-Business. 5 indexed citations
15.
Hernández‐Orallo, José, Peter Flach, & Cèsar Ferri. (2012). A unified view of performance metrics: translating threshold choice into expected classification loss. Journal of Machine Learning Research. 13(1). 2813–2869. 140 indexed citations
16.
Fuster, Vicente Domingo Estruch, Cèsar Ferri, José Hernández‐Orallo, & Marïa José Ramírez-Quintana. (2006). Similarity Functions for Structured Data. An Application to Decision Trees. INTELIGENCIA ARTIFICIAL. 10(29). 1 indexed citations
17.
Ferri, Cèsar, Peter Flach, & José Hernández‐Orallo. (2004). Delegating classifiers. 37–37. 45 indexed citations
18.
Ferri, Cèsar, Peter Flach, & José Hernández‐Orallo. (2003). Decision Trees for Ranking: Effect of New Smoothing Methods, New Splitting Criteria and Simple Pruning Methods. 5 indexed citations
19.
Albert, Elvira, Cèsar Ferri, Frank Steiner, & Germán Vidal. (2000). List-Processing Optimizations in a Multi-Paradigm Declarative Language.. 184–194.
20.
Ferri, Cèsar, José Hernández‐Orallo, & Marïa José Ramírez-Quintana. (2000). Learning functional logic classification concepts from databases.. 296–308. 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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