María Malfáz
- Social Psychology top 5%
- Artificial Intelligence top 5%
- Control and Systems Engineering top 5%
- Computer Vision and Pattern Recognition top 5%
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Miguel Á. SalichsÁlvaro Castro‐GonzálezFernándo Alonso-MartínJosé Carlos CastilloMarcos Maroto‐GómezRamón BarberJoão SequeiraAlaa Khamis
- Topics
- Social Robot Interaction and HRI (31 papers)Reinforcement Learning in Robotics (18 papers)Robotics and Automated Systems (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
- Partner nations
- SpainUnited KingdomNetherlands
In The Last Decade
María Malfáz
55 papers receiving 769 citations
Peers
Comparison fields: 5 of 84
- Social Psychology 387
- Artificial Intelligence 360
- Control and Systems Engineering 177
- Computer Vision and Pattern Recognition 169
- Experimental and Cognitive Psychology 116
Countries citing papers authored by María Malfáz
This map shows the geographic impact of María Malfáz'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 María Malfáz with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites María Malfáz more than expected).
Fields of papers citing papers by María Malfáz
This network shows the impact of papers produced by María Malfáz. 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 María Malfáz. The network helps show where María Malfáz may publish in the future.
Co-authorship network of co-authors of María Malfáz
This figure shows the co-authorship network connecting the top 25 collaborators of María Malfáz. A scholar is included among the top collaborators of María Malfáz 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 María Malfáz. María Malfáz 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 | 1 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | 1 | |
| 6 | 21 | |
| 7 | 3 | |
| 8 | 0 | |
| 9 | 7 | |
| 10 | 2 | |
| 11 | 2 | |
| 12 | 20 | |
| 13 | 13 | |
| 14 | 3 | |
| 15 | 1 | |
| 16 | 3 | |
| 17 | 5 | |
| 18 | 42 | |
| 19 | 5 | |
| 20 | Using Emotions for Behaviour-Selection Learning | 5 |
About María Malfáz
María Malfáz is a scholar working on Social Psychology, Artificial Intelligence and Control and Systems Engineering, having authored 57 papers that have together received 795 indexed citations. Recurring topics across this work include Social Robot Interaction and HRI (31 papers), Reinforcement Learning in Robotics (18 papers) and Robotics and Automated Systems (13 papers). The work is most often cited by research in Social Psychology (387 citations), Human-Computer Interaction (95 citations) and Artificial Intelligence (360 citations). María Malfáz has collaborated with scholars based in Spain, United Kingdom and Netherlands. Frequent co-authors include Miguel Á. Salichs, Álvaro Castro‐González, Fernándo Alonso-Martín, José Carlos Castillo, Marcos Maroto‐Gómez, Ramón Barber, João Sequeira, Alaa Khamis, Dolores Blanco and Santiago Garrido. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.