M. Concepción Ausín

37 total papers · 932 total citations
25 papers, 649 citations indexed

About

M. Concepción Ausín is a scholar working on Finance, Statistics and Probability and Artificial Intelligence. According to data from OpenAlex, M. Concepción Ausín has authored 25 papers receiving a total of 649 indexed citations (citations by other indexed papers that have themselves been cited), including 12 papers in Finance, 11 papers in Statistics and Probability and 10 papers in Artificial Intelligence. Recurrent topics in M. Concepción Ausín's work include Financial Risk and Volatility Modeling (12 papers), Bayesian Methods and Mixture Models (10 papers) and Probability and Risk Models (7 papers). M. Concepción Ausín is often cited by papers focused on Financial Risk and Volatility Modeling (12 papers), Bayesian Methods and Mixture Models (10 papers) and Probability and Risk Models (7 papers). M. Concepción Ausín collaborates with scholars based in Spain, United States and India. M. Concepción Ausín's co-authors include Michael P. Wiper, Ali Sarhadi, Pedro Galeano, Danielle Touma, Noah S. Diffenbaugh, Hedibert F. Lopes, Donald H. Burn, José Antonio Carranza Carnicero, Rosa E. Lillo and Pulak Ghosh and has published in prestigious journals such as Scientific Reports, Water Resources Research and European Journal of Operational Research.

In The Last Decade

M. Concepción Ausín

25 papers receiving 635 citations

Author Peers

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

Author						Papers	Cites
M. Concepción Ausín	290	165	112	112	99	25	649
Mauro Bernardi	180 0.6×	279 1.7×	62 0.6×	279 2.5×	18 0.2×	51	706
Alec Stephenson	410 1.4×	175 1.1×	36 0.3×	106 0.9×	17 0.2×	34	702
Carlo Gaetan	157 0.5×	93 0.6×	116 1.0×	158 1.4×	37 0.4×	50	734
Gabriel Frahm	146 0.5×	380 2.3×	37 0.3×	191 1.7×	18 0.2×	36	618
Marco Reale	98 0.3×	121 0.7×	109 1.0×	121 1.1×	36 0.4×	49	577
José Garcı́a Pérez	109 0.4×	109 0.7×	33 0.3×	206 1.8×	18 0.2×	56	727
Robert F. Dale	240 0.8×	36 0.2×	39 0.3×	20 0.2×	96 1.0×	47	670
Kunio Shimizu	119 0.4×	62 0.4×	166 1.5×	23 0.2×	18 0.2×	62	603
Paul J. Northrop	510 1.8×	80 0.5×	16 0.1×	62 0.6×	22 0.2×	22	710
Magnus Ekström	181 0.6×	34 0.2×	45 0.4×	40 0.4×	94 0.9×	55	726

Countries citing papers authored by M. Concepción Ausín

Since Specialization

Citations

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

Fields of papers citing papers by M. Concepción Ausín

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. Concepción Ausín. 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 M. Concepción Ausín. The network helps show where M. Concepción Ausín may publish in the future.

Co-authorship network of co-authors of M. Concepción Ausín

This figure shows the co-authorship network connecting the top 25 collaborators of M. Concepción Ausín. A scholar is included among the top collaborators of M. Concepción Ausín 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 M. Concepción Ausín. M. Concepción Ausín 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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