Roberto Torres

530 citations
10 papers · 281 · h-index 7

Impact in

Papers in

Roberto Torres

10 papers receiving 248 citations

Peers

Roberto Torres
Comparison fields: 5 of 59
  • Information Systems 163
  • Statistics, Probability and Uncertainty 27
  • Artificial Intelligence 122
  • Management Science and Operations Research 36
  • Computer Graphics and Computer-Aided Design 10
Replace Qizhen Zhang with:
Qizhen Zhang United States
Jörg Kindermann Germany
Kuldeep S. Meel Singapore
Kee Siong Ng Australia
M. J. R. Shave United Kingdom
Javad Azimi United States
K. Weidenhaupt Germany
Jianjun Yu China
Jennifer Gillenwater United States
Sam Yuan Sung Singapore
Roberto Torres relative to Qizhen Zhang United States Qizhen Zhang's profile →
Citations per field
00.5×3.3×
Qizhen Zhang · 1×
Citations per year

Countries citing papers authored by Roberto Torres

Since Specialization
Citations

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

Fields of papers citing papers by Roberto Torres

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 14 scholars most cited alongside Roberto Torres, 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 Roberto Torres Line = papers co-authored together Roberto Torres links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1 2004160
2 200638
3 201224
4
Lessons on applying automated recommender systems to information-seeking tasks
200623
5
Towards Combining Probabilistic and Interval Uncertainty in Engineering Calculations
200413
6 20099
7 20048
8 20193
9 20042
10 20111

About Roberto Torres

Roberto Torres is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Computer Networks and Communications, Information Systems and Signal Processing, having authored 10 papers that have together received 281 indexed citations. Recurring topics across this work include Geographic Information Systems Studies (2 papers), Recommender Systems and Techniques (2 papers), Data Management and Algorithms (2 papers), Probabilistic and Robust Engineering Design (2 papers), Computer Graphics and Visualization Techniques (2 papers), Numerical Methods and Algorithms (2 papers), Medical Image Segmentation Techniques (1 paper) and Advanced Vision and Imaging (1 paper). The work is most often cited by research in Information Systems (163 citations), Statistics, Probability and Uncertainty (27 citations), Artificial Intelligence (122 citations), Management Science and Operations Research (36 citations) and Computer Graphics and Computer-Aided Design (10 citations). Roberto Torres has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Sean M. McNee, John Riedl, Joseph A. Konstan, Mara Abel, Luc Longpré, Владик Крейнович, Scott A. Starks, Gang Xiang, Jan Beck and Martine Ceberio. Their work appears in journals such as Reliable Computing, Revista Tecnica De La Facultad De Ingenieria Universidad Del Zulia, scholarworks - UTEP (The University of Texas at El Paso) and National Conference on Artificial Intelligence.

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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