Katia Vega
- Human-Computer Interaction top 0.5%
- Biomedical Engineering
- Cognitive Neuroscience top 10%
- Electrical and Electronic Engineering
- Mechanical Engineering
- Co-authors
- Eldy S. Lazaro VasquezHugo FukśPattie MaesJoe ParadisoAli K. YetisenHao‐Chuan WangHsin-Liu KaoXin Liu
- Topics
- Interactive and Immersive Displays (16 papers)Innovative Human-Technology Interaction (12 papers)Advanced Sensor and Energy Harvesting Materials (11 papers)
- Journals
- Angewandte Chemie International EditionSHILAP Revista de lepidopterologíaComputer
- Partner nations
- United StatesBrazilUnited Kingdom
In The Last Decade
Katia Vega
44 papers receiving 723 citations
Peers
Comparison fields: 5 of 97
- Human-Computer Interaction 426
- Biomedical Engineering 253
- Cognitive Neuroscience 217
- Electrical and Electronic Engineering 82
- Mechanical Engineering 67
Countries citing papers authored by Katia Vega
This map shows the geographic impact of Katia Vega'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 Katia Vega with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Katia Vega more than expected).
Fields of papers citing papers by Katia Vega
This network shows the impact of papers produced by Katia Vega. 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 Katia Vega. The network helps show where Katia Vega may publish in the future.
Co-authorship network of co-authors of Katia Vega
This figure shows the co-authorship network connecting the top 25 collaborators of Katia Vega. A scholar is included among the top collaborators of Katia Vega 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 Katia Vega. Katia Vega 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 | 2 | |
| 3 | 2 | |
| 4 | 2 | |
| 5 | 9 | |
| 6 | 4 | |
| 7 | 1 | |
| 8 | 14 | |
| 9 | 75 | |
| 10 | 31 | |
| 11 | 1 | |
| 12 | 8 | |
| 13 | 12 | |
| 14 | 3 | |
| 15 | 8 | |
| 16 | 1 | |
| 17 | 2 | |
| 18 | The Web of Things as an Infrastructure for Improving Users’ Health and Wellbeing | 1 |
| 19 | 9 | |
| 20 | 6 |
About Katia Vega
Katia Vega is a scholar working on Human-Computer Interaction, Cognitive Neuroscience and Biomedical Engineering, having authored 49 papers that have together received 738 indexed citations. Recurring topics across this work include Interactive and Immersive Displays (16 papers), Innovative Human-Technology Interaction (12 papers) and Advanced Sensor and Energy Harvesting Materials (11 papers). The work is most often cited by research in Human-Computer Interaction (426 citations), Cognitive Neuroscience (217 citations) and Museology (35 citations). Katia Vega has collaborated with scholars based in United States, Brazil and United Kingdom. Frequent co-authors include Eldy S. Lazaro Vasquez, Hugo Fukś, Pattie Maes, Joe Paradiso, Ali K. Yetisen, Hao‐Chuan Wang, Hsin-Liu Kao, Xin Liu, Joseph A. Paradiso and Nan Jiang. Their work appears in journals such as Angewandte Chemie International Edition, SHILAP Revista de lepidopterología and Computer.
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.