This map shows the geographic impact of Ulises Cortés'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 Ulises Cortés with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ulises Cortés more than expected).
This network shows the impact of papers produced by Ulises Cortés. 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 Ulises Cortés. The network helps show where Ulises Cortés may publish in the future.
Co-authorship network of co-authors of Ulises Cortés
This figure shows the co-authorship network connecting the top 25 collaborators of Ulises Cortés.
A scholar is included among the top collaborators of Ulises Cortés 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 Ulises Cortés. Ulises Cortés is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
García-Gasulla, Dario, Javier Alonso, Ulises Cortés, Eduard Ayguadé, & Jesús Labarta. (2015). Extracting Visual Patterns from Deep Learning Representations.. arXiv (Cornell University).3 indexed citations
6.
Kusumawardani, Sri Suning, et al.. (2014). REDUCING STUDENT'S LEARNING DURATION ON ENGINEERING FINAL PROJECT BY IMPLEMENTING FINK'S TAXONOMY ON E-LEARNING. Journal of Theoretical and Applied Information Technology. 68(3). 375–380.
7.
García-Gasulla, Dario & Ulises Cortés. (2014). Link prediction in very large directed graphs: Exploiting hierarchical properties in parallel. RECERCAT (Consorci de Serveis Universitaris de Catalunya). 1–13.2 indexed citations
Cofré, Hernán, et al.. (2009). Frecuencia y tipo de actividades de laboratorio que realizan profesores/as primarios en el area de las ciencias, en Santiago de Chile. Enseñanza de las ciencias: revista de investigación y experiencias didácticas. 3420–3423.1 indexed citations
10.
Rodríguez‐Roda, Ignasi, et al.. (2009). Using Meta-Cases to Improve Accuracy in Hierarchical Case Retrieval. Computación y Sistemas. 4(1). 53–63.1 indexed citations
Nieves, Juan Carlos, Mauricio Osorio, Ulises Cortés, Francisco Caballero, & A López‐Navidad. (2007). Reasoning about actions under uncertainty: A possibilistic approach. 300–309.2 indexed citations
13.
Modgil, Sanjay, et al.. (2006). Argument Schemes and Critical Questions for Heterogeneous Agents to Argue over the Viability of a Human Organ for Transplantation.. National Conference on Artificial Intelligence. 105.8 indexed citations
14.
Martínez, Montse, Ignasi Rodríguez‐Roda, Manel Poch, Ulises Cortés, & Joaquím Comas. (2004). Dynamic reasoning to solve complex problems in activated sludge processes: a step further in Decision Support Systems. Lund University Publications (Lund University).
15.
Poch, Manel, et al.. (2004). An Environmental Decision Support System to Identify the most Appropriate Wastewater Treatment Process. From Catalonia to Latin America. Research in computing science. 11. 15–29.1 indexed citations
16.
Cortés, Ulises, Montse Martínez, Joaquím Comas, et al.. (2003). A conceptual model to facilitate knowledge sharing for bulking solving in wastewater treatment plants. AI Communications. 16(4). 279–289.10 indexed citations
17.
Vázquez-Salceda, Javier, Ulises Cortés, Julián Padget, A López‐Navidad, & Francisco Caballero. (2003). The organ allocation process: a natural extension of the Carrel Agent-Mediated Electronic Institution. AI Communications. 16(3). 153–165.12 indexed citations
Alonso, Javier & Ulises Cortés. (1998). Experiments with Domain Knowledge in Unsupervised Learning: Using and Revising Theories. Computación y Sistemas. 1(3). 136–144.2 indexed citations
20.
Sangüesa, Ramón & Ulises Cortés. (1997). Learning causal networks from datac a survey and a new algorithm for recovering possibilistic causal networks. AI Communications. 10(1). 31–61.18 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.