Daniel E. Acuña

35 papers receiving 761 citations

Peers

Daniel E. Acuña
Comparison fields: 5 of 117
  • Statistics, Probability and Uncertainty 209
  • General Decision Sciences 23
  • Cognitive Neuroscience 205
  • Information Systems and Management 57
  • Health Informatics 11
Replace Frank Goldhammer with:
Frank Goldhammer Germany
Richard Tobin United Kingdom
David G. Dobolyi United States
Xiaofei Lu United States
Linda S. Steinberg United States
Paul R. Smart United Kingdom
Tessa Verhoef Netherlands
Marsha C. Lovett United States
Cengiz Acartürk Türkiye
André Tricot France
Daniel E. Acuña relative to Frank Goldhammer Germany Frank Goldhammer's profile →
Citations per field
00.5×9.5×
Frank Goldhammer · 1×
Citations per year

Countries citing papers authored by Daniel E. Acuña

Since Specialization
Citations

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

Fields of papers citing papers by Daniel E. Acuña

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daniel E. Acuña. 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 Daniel E. Acuña. The network helps show where Daniel E. Acuña may publish in the future.

Co-authors

The 25 scholars most cited alongside Daniel E. Acuña, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Daniel E. Acuña Line = papers co-authored together Daniel E. Acuña links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 37 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2012151
2 201673
3 201671
4 201870
5 201869
6 201045
7 201543
8 201241
9 201438
10
Bayesian modeling of human sequential decision-making on the multi-armed bandit problem
200819
11 202219
12 202317
13 202015
14 201812
15 201011
16 202211
17 202011
18 202011
19 20229
20 20168

About Daniel E. Acuña

Daniel E. Acuña is a scholar working on Statistics, Probability and Uncertainty, General Decision Sciences, Health Informatics, Information Systems and Management and History and Philosophy of Science, having authored 37 papers that have together received 791 indexed citations. Recurring topics across this work include scientometrics and bibliometrics research (10 papers), Topic Modeling (6 papers), Health and Medical Research Impacts (3 papers), Neural and Behavioral Psychology Studies (3 papers), Natural Language Processing Techniques (3 papers), Scientific Computing and Data Management (3 papers), Motor Control and Adaptation (3 papers) and Advanced Text Analysis Techniques (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (209 citations), General Decision Sciences (23 citations), Cognitive Neuroscience (205 citations), Information Systems and Management (57 citations) and Health Informatics (11 citations). Daniel E. Acuña has collaborated with scholars based in United States, China and Australia. Frequent co-authors include Konrad P. Körding, Stefano Allesina, Titipat Achakulvisut, Max Berniker, Scott T. Grafton, Stephen V. David, Jean Liénard, Hugo L. Fernandes, Robert S. Turner and James A. Evans. Their work appears in journals such as PLoS ONE, Nature Communications, PLoS Computational Biology, Journal of Informetrics and Scientometrics.

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.

Explore authors with similar magnitude of impact

Rankless by CCL
2026