Sergio A. Navarro-Tuch
- Education top 5%
- Information Systems top 5%
- Computer Science Applications top 5%
- Biomedical Engineering
- Industrial and Manufacturing Engineering top 10%
- Co-authors
- Rogelio Bustamante-BelloArturo MolinaJulieta NoguezMaría SoledadJhonattan MirandaJavier Izquierdo-ReyesHéctor Pérez-MeanaRicardo A. Ramírez-Mendoza
- Topics
- Emotion and Mood Recognition (6 papers)Color perception and design (4 papers)Autonomous Vehicle Technology and Safety (3 papers)
- Journals
- SHILAP Revista de lepidopterologíaIEEE AccessSensors
- Partner nations
- MexicoUnited KingdomUnited States
In The Last Decade
Sergio A. Navarro-Tuch
19 papers receiving 461 citations
Hit Papers
Peers
Comparison fields: 5 of 99
- Education 153
- Information Systems 126
- Computer Science Applications 77
- Biomedical Engineering 57
- Industrial and Manufacturing Engineering 50
Countries citing papers authored by Sergio A. Navarro-Tuch
This map shows the geographic impact of Sergio A. Navarro-Tuch'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 Sergio A. Navarro-Tuch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Sergio A. Navarro-Tuch more than expected).
Fields of papers citing papers by Sergio A. Navarro-Tuch
This network shows the impact of papers produced by Sergio A. Navarro-Tuch. 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 Sergio A. Navarro-Tuch. The network helps show where Sergio A. Navarro-Tuch may publish in the future.
Co-authorship network of co-authors of Sergio A. Navarro-Tuch
This figure shows the co-authorship network connecting the top 25 collaborators of Sergio A. Navarro-Tuch. A scholar is included among the top collaborators of Sergio A. Navarro-Tuch 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 Sergio A. Navarro-Tuch. Sergio A. Navarro-Tuch is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 19 | |
| 3 | 8 | |
| 4 | 0 | |
| 5 | 41 | |
| 6 | 24 | |
| 7 | The core components of education 4.0 in higher education: Three case studies in engineering educationbreakdown → | 316 |
| 8 | 3 | |
| 9 | 3 | |
| 10 | 9 | |
| 11 | 4 | |
| 12 | 1 | |
| 13 | 9 | |
| 14 | 5 | |
| 15 | 0 | |
| 16 | 4 | |
| 17 | 10 | |
| 18 | 1 | |
| 19 | 26 | |
| 20 | 4 |
About Sergio A. Navarro-Tuch
Sergio A. Navarro-Tuch is a scholar working on Experimental and Cognitive Psychology, Computer Science Applications and Human-Computer Interaction, having authored 23 papers that have together received 489 indexed citations. Recurring topics across this work include Emotion and Mood Recognition (6 papers), Color perception and design (4 papers) and Autonomous Vehicle Technology and Safety (3 papers). The work is most often cited by research in Computer Science Applications (77 citations), Information Systems (126 citations) and Education (153 citations). Sergio A. Navarro-Tuch has collaborated with scholars based in Mexico, United Kingdom and United States. Frequent co-authors include Rogelio Bustamante-Bello, Arturo Molina, Julieta Noguez, María Soledad, Jhonattan Miranda, Javier Izquierdo-Reyes, Héctor Pérez-Meana, Ricardo A. Ramírez-Mendoza, Luis Montesinos and Omar Hernández‐González. Their work appears in journals such as SHILAP Revista de lepidopterología, IEEE Access and Sensors.
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.