Pedro Ubilla

88 total papers · 1.0k total citations
57 papers, 713 citations indexed

About

Pedro Ubilla is a scholar working on Applied Mathematics, Computational Theory and Mathematics and Mathematical Physics. According to data from OpenAlex, Pedro Ubilla has authored 57 papers receiving a total of 713 indexed citations (citations by other indexed papers that have themselves been cited), including 57 papers in Applied Mathematics, 42 papers in Computational Theory and Mathematics and 15 papers in Mathematical Physics. Recurrent topics in Pedro Ubilla's work include Nonlinear Partial Differential Equations (52 papers), Advanced Mathematical Modeling in Engineering (42 papers) and Nonlinear Differential Equations Analysis (30 papers). Pedro Ubilla is often cited by papers focused on Nonlinear Partial Differential Equations (52 papers), Advanced Mathematical Modeling in Engineering (42 papers) and Nonlinear Differential Equations Analysis (30 papers). Pedro Ubilla collaborates with scholars based in Chile, Brazil and Belgium. Pedro Ubilla's co-authors include Djairo G. de Figueiredo, Jean–Pierre Gossez, João Marcos do Ó, Sebastián Lorca, Marta García‐Huidobro, Friedemann Brock, Bernhard Ruf, Raúl Manásevich, Ederson Moreira dos Santos and Marco A. S. Souto and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of Mathematical Analysis and Applications and Journal of Differential Equations.

In The Last Decade

Pedro Ubilla

52 papers receiving 639 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Pedro Ubilla 695 533 180 78 52 57 713
Marta García‐Huidobro 679 1.0× 518 1.0× 243 1.4× 121 1.6× 69 1.3× 70 733
Petru Jebelean 743 1.1× 429 0.8× 168 0.9× 166 2.1× 39 0.8× 60 775
Marcelo Montenegro 763 1.1× 663 1.2× 304 1.7× 146 1.9× 67 1.3× 79 858
Roberta Musina 606 0.9× 449 0.8× 260 1.4× 50 0.6× 59 1.1× 57 659
Atsushi Tachikawa 641 0.9× 512 1.0× 250 1.4× 54 0.7× 70 1.3× 38 702
Igor E. Verbitsky 720 1.0× 295 0.6× 412 2.3× 42 0.5× 39 0.8× 39 774
Lorenzo D’Ambrosio 571 0.8× 340 0.6× 262 1.5× 25 0.3× 50 1.0× 34 633
Antonio Iannizzotto 689 1.0× 509 1.0× 151 0.8× 119 1.5× 61 1.2× 48 720
Giovanni Cupini 587 0.8× 481 0.9× 264 1.5× 48 0.6× 50 1.0× 45 639
Yuxia Guo 658 0.9× 510 1.0× 377 2.1× 66 0.8× 116 2.2× 103 769

Countries citing papers authored by Pedro Ubilla

Since Specialization
Citations

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

Fields of papers citing papers by Pedro Ubilla

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Pedro Ubilla

This figure shows the co-authorship network connecting the top 25 collaborators of Pedro Ubilla. A scholar is included among the top collaborators of Pedro Ubilla 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 Pedro Ubilla. Pedro Ubilla is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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