Rafael Rumí

1.9k total citations · 1 hit paper
43 papers, 1.2k citations indexed

About

Rafael Rumí is a scholar working on Artificial Intelligence, Global and Planetary Change and Signal Processing. According to data from OpenAlex, Rafael Rumí has authored 43 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Artificial Intelligence, 8 papers in Global and Planetary Change and 6 papers in Signal Processing. Recurrent topics in Rafael Rumí's work include Bayesian Modeling and Causal Inference (31 papers), Bayesian Methods and Mixture Models (13 papers) and Data Management and Algorithms (6 papers). Rafael Rumí is often cited by papers focused on Bayesian Modeling and Causal Inference (31 papers), Bayesian Methods and Mixture Models (13 papers) and Data Management and Algorithms (6 papers). Rafael Rumí collaborates with scholars based in Spain, Denmark and United States. Rafael Rumí's co-authors include Antonio Salmerón, Pedro A. Aguilera, Antonio Fernández, Rosa Fernández, Helge Langseth, Thomas D. Nielsen, Barry R. Cobb, Prakash P. Shenoy, Serafı́n Moral and Anders L. Madsen and has published in prestigious journals such as International Journal of Production Economics, Ecological Modelling and Decision Support Systems.

In The Last Decade

Rafael Rumí

41 papers receiving 1.1k citations

Hit Papers

Bayesian networks in environmental modelling 2011 2026 2016 2021 2011 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Rafael Rumí Spain 14 507 274 148 144 127 43 1.2k
Antonio Salmerón Spain 19 835 1.6× 258 0.9× 145 1.0× 134 0.9× 227 1.8× 88 1.6k
Anders L. Madsen Denmark 16 627 1.2× 263 1.0× 129 0.9× 55 0.4× 200 1.6× 66 1.6k
Antonio Fernández Spain 22 377 0.7× 249 0.9× 171 1.2× 147 1.0× 52 0.4× 71 1.8k
Kjersti Aas Norway 18 433 0.9× 435 1.6× 168 1.1× 143 1.0× 277 2.2× 40 2.8k
Coşkun Özkan Türkiye 20 180 0.4× 306 1.1× 262 1.8× 126 0.9× 294 2.3× 62 1.6k
Richard D. De Veaux United States 13 176 0.3× 115 0.4× 172 1.2× 41 0.3× 58 0.5× 37 936
Annukka Lehikoinen Finland 16 138 0.3× 353 1.3× 174 1.2× 150 1.0× 78 0.6× 38 1.2k
Ren Zhang China 19 236 0.5× 230 0.8× 118 0.8× 45 0.3× 402 3.2× 100 1.3k
Zhengyuan Zhu United States 23 205 0.4× 466 1.7× 626 4.2× 84 0.6× 62 0.5× 99 1.5k
İnci Batmaz Türkiye 14 164 0.3× 158 0.6× 117 0.8× 53 0.4× 142 1.1× 32 1.1k

Countries citing papers authored by Rafael Rumí

Since Specialization
Citations

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

Fields of papers citing papers by Rafael Rumí

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Rafael Rumí

This figure shows the co-authorship network connecting the top 25 collaborators of Rafael Rumí. A scholar is included among the top collaborators of Rafael Rumí 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 Rafael Rumí. Rafael Rumí 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.
Flores, M. Julia, et al.. (2024). Flash floods in Mediterranean catchments: a meta-model decision support system based on Bayesian networks. Environmental and Ecological Statistics. 31(1). 27–56. 3 indexed citations
2.
Flores, M. Julia, et al.. (2022). Bayesian Networks for Preprocessing Water Management Data. Mathematics. 10(10). 1777–1777. 2 indexed citations
3.
Salmerón, Antonio, et al.. (2022). An Empirical Analysis of the Impact of Continuous Assessment on the Final Exam Mark. Mathematics. 10(21). 3994–3994. 3 indexed citations
4.
Maldonado, Ana D., et al.. (2021). A Soft Clustering Approach to Detect Socio-Ecological Landscape Boundaries Using Bayesian Networks. Agronomy. 11(4). 740–740. 3 indexed citations
5.
Flores, M. Julia, et al.. (2019). Assessment of flood risk in Mediterranean catchments: an approach based on Bayesian networks. Stochastic Environmental Research and Risk Assessment. 33(11-12). 1991–2005. 8 indexed citations
6.
7.
Nicholson, Ann E., et al.. (2018). Learning and inference methodologies for hybrid dynamic Bayesian networks: a case study for a water reservoir system in Andalusia, Spain. Stochastic Environmental Research and Risk Assessment. 32(11). 3117–3135. 7 indexed citations
8.
Rumí, Rafael, et al.. (2018). Bayesian networks for evaluating climate change influence in olive crops in Andalusia, Spain. Natural Resource Modeling. 32(1). 8 indexed citations
9.
Masegosa, Andrés R., Antonio Salmerón, Rafael Rumí, et al.. (2018). Scalable importance sampling estimation of Gaussian mixture posteriors in Bayesian networks. International Journal of Approximate Reasoning. 100. 115–134. 7 indexed citations
10.
Shenoy, Prakash P., Rafael Rumí, & Antonio Salmerón. (2014). Practical Aspects of Solving Hybrid Bayesian Networks Containing Deterministic Conditionals. International Journal of Intelligent Systems. 30(3). 265–291. 6 indexed citations
11.
Fernández, Antonio, Rafael Rumí, & Antonio Salmerón. (2012). Answering queries in hybrid Bayesian networks using importance sampling. Decision Support Systems. 53(3). 580–590. 6 indexed citations
12.
Langseth, Helge, Thomas D. Nielsen, Rafael Rumí, & Antonio Salmerón. (2011). Mixtures of truncated basis functions. International Journal of Approximate Reasoning. 53(2). 212–227. 48 indexed citations
13.
Nielsen, Jens Frederik Dalsgaard, Rafael Rumí, & Antonio Salmerón. (2010). Structural-EM for learning PDG models from incomplete data. International Journal of Approximate Reasoning. 51(5). 515–530. 6 indexed citations
14.
Langseth, Helge, Thomas D. Nielsen, Rafael Rumí, & Antonio Salmerón. (2010). Parameter estimation and model selection for mixtures of truncated exponentials. International Journal of Approximate Reasoning. 51(5). 485–498. 23 indexed citations
15.
Langseth, Helge, Thomas D. Nielsen, Rafael Rumí, & Antonio Salmerón. (2008). Parameter Estimation in Mixtures of Truncated Exponentials. VBN Forskningsportal (Aalborg Universitet). 169–176. 2 indexed citations
16.
Nielsen, Jens Perch, Rafael Rumí, & Antonio Salmerón. (2007). El Clasificador Grafo de Decisión Probabilístico. 273. 1 indexed citations
17.
Gámez, José A., Rafael Rumí, & Antonio Salmerón. (2006). Unsupervised naive Bayes for data clustering with mixtures of truncated exponentials. 123–130. 4 indexed citations
18.
Rumí, Rafael & Antonio Salmerón. (2006). Approximate probability propagation with mixtures of truncated exponentials. International Journal of Approximate Reasoning. 45(2). 191–210. 36 indexed citations
19.
Rumí, Rafael, et al.. (2005). Learning hybrid Bayesian networks using mixtures of truncated exponentials. International Journal of Approximate Reasoning. 42(1-2). 54–68. 40 indexed citations
20.
Moral, Serafı́n, Rafael Rumí, & Antonio Salmerón. (2002). Estimating mixtures of truncated exponentials from data. Repositorio de Patentes de la Universidad de Almería (Universidad de Almería). 15 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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