José A. Lozano

15.8k citations
292 papers · 10.4k indexed · 5 hit papers · h-index 45

José A. Lozano

277 papers receiving 9.9k citations

Hit Papers

A Review of Auto-scaling Techniques f...45219992026200820174008001.2k

Peers

José A. Lozano
Comparison fields: 5 of 220
  • Artificial Intelligence 4.4k
  • Industrial and Manufacturing Engineering 802
  • Computational Theory and Mathematics 1.2k
  • Signal Processing 786
  • Computer Vision and Pattern Recognition 1.0k
Replace Javier Del Ser with:
Javier Del Ser Spain
Frank Hutter Germany
Tim Blackwell United Kingdom
Pedro Larrañaga Spain
Nal Kalchbrenner United Kingdom
Sotiris Kotsiantis Greece
Oded Maimon Israel
Václav Snåšel Czechia
Jyh‐Shing Roger Jang Taiwan
Zong Woo Geem South Korea
José A. Lozano relative to Javier Del Ser Spain Javier Del Ser's profile →
Citations per field
00.5×3.3×
Javier Del Ser · 1×
Citations per year

Countries citing papers authored by José A. Lozano

Since Specialization
Citations

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

Fields of papers citing papers by José A. Lozano

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by José A. Lozano. 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 José A. Lozano. The network helps show where José A. Lozano may publish in the future.

Co-authorship network

The 25 scholars most cited alongside José A. Lozano, 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 José A. Lozano Line = papers co-authored together José A. Lozano links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20240
2 20242
3 20235
4 20232
5 20231
6 20231
7 20231
8 20238
9 20233
10 20222
11 20227
12 20220
13 201943
14
Mateda-2.0: A MATLAB Package for the Implementation and Analysis of Estimation of Distribution Algorithms
20101
15 200953
16 200442
17 200419
18 200316
19
Unsupervised Learning of Bayesian Networks Via Estimation of Distribution Algorithms.
20023
20 200025

About José A. Lozano

José A. Lozano is a scholar working on Artificial Intelligence, Signal Processing and Industrial and Manufacturing Engineering, having authored 292 papers that have together received 10.4k indexed citations. Recurring topics across this work include Metaheuristic Optimization Algorithms Research (58 papers), Bayesian Modeling and Causal Inference (44 papers), Evolutionary Algorithms and Applications (29 papers), Anomaly Detection Techniques and Applications (26 papers), Bayesian Methods and Mixture Models (22 papers), Time Series Analysis and Forecasting (20 papers), Machine Learning and Data Classification (18 papers) and Advanced Multi-Objective Optimization Algorithms (18 papers). The work is most often cited by research in Artificial Intelligence (4.4k citations), Industrial and Manufacturing Engineering (802 citations) and Computational Theory and Mathematics (1.2k citations). José A. Lozano has collaborated with scholars based in Spain, United Kingdom and United States. Frequent co-authors include Pedro Larrañaga, Aritz Pérez, Juan Diego Rodríguez, Iñaki Inza, Alexander Mendiburu, José M. Peña, Roberto Santana, José Miguel-Alonso, Tania Lorido-Botrán and Usue Mori. Their work appears in journals such as Nucleic Acids Research, SHILAP Revista de lepidopterología and Renewable and Sustainable Energy Reviews.

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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