Marcelino Lázaro
- Artificial Intelligence top 5%
- Electrical and Electronic Engineering
- Signal Processing top 5%
- Control and Systems Engineering top 10%
- Computational Mechanics
- Co-authors
- Ignacio Santamarı́aAnı́bal R. Figueiras-VidalC. PantaleónDeniz ErdoğmuşJosé C. Prı́ncipeAntonio Artés-Rodrı́guezKenneth E. HildFrancisco Herrera
- Topics
- Neural Networks and Applications (13 papers)Blind Source Separation Techniques (8 papers)Distributed Sensor Networks and Detection Algorithms (6 papers)
- Partner nations
- SpainUnited StatesUnited Kingdom
In The Last Decade
Marcelino Lázaro
38 papers receiving 396 citations
Peers
Comparison fields: 5 of 62
- Artificial Intelligence 204
- Electrical and Electronic Engineering 146
- Signal Processing 106
- Control and Systems Engineering 77
- Computational Mechanics 58
Countries citing papers authored by Marcelino Lázaro
This map shows the geographic impact of Marcelino Lázaro'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 Marcelino Lázaro with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marcelino Lázaro more than expected).
Fields of papers citing papers by Marcelino Lázaro
This network shows the impact of papers produced by Marcelino Lázaro. 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 Marcelino Lázaro. The network helps show where Marcelino Lázaro may publish in the future.
Co-authorship network of co-authors of Marcelino Lázaro
This figure shows the co-authorship network connecting the top 25 collaborators of Marcelino Lázaro. A scholar is included among the top collaborators of Marcelino Lázaro 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 Marcelino Lázaro. Marcelino Lázaro is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 17 | |
| 2 | 3 | |
| 3 | 13 | |
| 4 | 11 | |
| 5 | 4 | |
| 6 | 14 | |
| 7 | 1 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 3 | |
| 11 | 7 | |
| 12 | 1 | |
| 13 | 2 | |
| 14 | 38 | |
| 15 | 28 | |
| 16 | 16 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 17 | |
| 20 | 10 |
About Marcelino Lázaro
Marcelino Lázaro is a scholar working on Signal Processing, Artificial Intelligence and Analytical Chemistry, having authored 39 papers that have together received 418 indexed citations. Recurring topics across this work include Neural Networks and Applications (13 papers), Blind Source Separation Techniques (8 papers) and Distributed Sensor Networks and Detection Algorithms (6 papers). The work is most often cited by research in Signal Processing (106 citations), Artificial Intelligence (204 citations) and Control and Systems Engineering (77 citations). Marcelino Lázaro has collaborated with scholars based in Spain, United States and United Kingdom. Frequent co-authors include Ignacio Santamarı́a, Anı́bal R. Figueiras-Vidal, C. Pantaleón, Deniz Erdoğmuş, José C. Prı́ncipe, Antonio Artés-Rodrı́guez, Kenneth E. Hild, Francisco Herrera, Fernando Pérez‐Cruz and Salvador García. Their work appears in journals such as IEEE Transactions on Signal Processing, Expert Systems with Applications and Pattern Recognition.
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.