Pétia Georgieva
- Control and Systems Engineering top 5%
- Artificial Intelligence top 10%
- Materials Chemistry
- Cognitive Neuroscience top 10%
- Mechanical Engineering
- Co-authors
- S. Feyo de AzevedoPetia Koprinkova‐HristovaA. Andrade‐CamposIsabel M. SantosAchim IlchmannSudipta SealE.B. MartinA.J. Morris
- Topics
- Advanced Control Systems Optimization (20 papers)EEG and Brain-Computer Interfaces (14 papers)Fault Detection and Control Systems (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaPLoS ONEScientific Reports
- Partner nations
- PortugalBulgariaUnited States
In The Last Decade
Pétia Georgieva
92 papers receiving 863 citations
Peers
Comparison fields: 5 of 138
- Control and Systems Engineering 222
- Artificial Intelligence 159
- Materials Chemistry 153
- Cognitive Neuroscience 153
- Mechanical Engineering 133
Countries citing papers authored by Pétia Georgieva
This map shows the geographic impact of Pétia Georgieva'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 Pétia Georgieva with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pétia Georgieva more than expected).
Fields of papers citing papers by Pétia Georgieva
This network shows the impact of papers produced by Pétia Georgieva. 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 Pétia Georgieva. The network helps show where Pétia Georgieva may publish in the future.
Co-authorship network of co-authors of Pétia Georgieva
This figure shows the co-authorship network connecting the top 25 collaborators of Pétia Georgieva. A scholar is included among the top collaborators of Pétia Georgieva 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 Pétia Georgieva. Pétia Georgieva is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 15 | |
| 3 | 8 | |
| 4 | 1 | |
| 5 | 2 | |
| 6 | 2 | |
| 7 | 9 | |
| 8 | 0 | |
| 9 | 1 | |
| 10 | 0 | |
| 11 | 15 | |
| 12 | 6 | |
| 13 | 23 | |
| 14 | 45 | |
| 15 | 9 | |
| 16 | Application of artificial neural networks in modeling and optimization of batch crystallization processes | 2 |
| 17 | Aplicação de técnicas de aprendizagem automática para classificação de emoções humanas com sinais de EEG | 1 |
| 18 | Linear invariant systems theory for signal enhancement | 1 |
| 19 | 1 | |
| 20 | 3 |
About Pétia Georgieva
Pétia Georgieva is a scholar working on Space and Planetary Science, Control and Systems Engineering and Acoustics and Ultrasonics, having authored 101 papers that have together received 915 indexed citations. Recurring topics across this work include Advanced Control Systems Optimization (20 papers), EEG and Brain-Computer Interfaces (14 papers) and Fault Detection and Control Systems (13 papers). The work is most often cited by research in Control and Systems Engineering (222 citations), Cognitive Neuroscience (153 citations) and Experimental and Cognitive Psychology (80 citations). Pétia Georgieva has collaborated with scholars based in Portugal, Bulgaria and United States. Frequent co-authors include S. Feyo de Azevedo, Petia Koprinkova‐Hristova, A. Andrade‐Campos, Isabel M. Santos, Achim Ilchmann, Sudipta Seal, E.B. Martin, A.J. Morris, Arvind Agarwal and S. C. Kuiry. Their work appears in journals such as SHILAP Revista de lepidopterología, PLoS ONE and Scientific Reports.
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.