Dimitar Shterionov
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition
- Human-Computer Interaction top 10%
- Language and Linguistics top 10%
- Developmental and Educational Psychology
- Co-authors
- Andy WayEva VanmassenhoveAlberto PoncelasChris EmmeryPeyman PassbanDeclan GrovesJoss MoorkensJoachim Wagner
- Topics
- Natural Language Processing Techniques (15 papers)Topic Modeling (12 papers)Hand Gesture Recognition Systems (5 papers)
- Partner nations
- NetherlandsIrelandBelgium
In The Last Decade
Dimitar Shterionov
23 papers receiving 174 citations
Peers
Comparison fields: 5 of 34
- Artificial Intelligence 157
- Computer Vision and Pattern Recognition 48
- Human-Computer Interaction 36
- Language and Linguistics 29
- Developmental and Educational Psychology 25
Countries citing papers authored by Dimitar Shterionov
This map shows the geographic impact of Dimitar Shterionov'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 Dimitar Shterionov with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dimitar Shterionov more than expected).
Fields of papers citing papers by Dimitar Shterionov
This network shows the impact of papers produced by Dimitar Shterionov. 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 Dimitar Shterionov. The network helps show where Dimitar Shterionov may publish in the future.
Co-authorship network of co-authors of Dimitar Shterionov
This figure shows the co-authorship network connecting the top 25 collaborators of Dimitar Shterionov. A scholar is included among the top collaborators of Dimitar Shterionov 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 Dimitar Shterionov. Dimitar Shterionov 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 | 8 | |
| 4 | 1 | |
| 5 | 7 | |
| 6 | 1 | |
| 7 | 8 | |
| 8 | 0 | |
| 9 | 19 | |
| 10 | 7 | |
| 11 | 25 | |
| 12 | An Investigative Study of Multi-Modal Cross-Lingual Retrieval | 2 |
| 13 | 6 | |
| 14 | ABI Neural Ensemble Model for Gender Prediction. | 1 |
| 15 | 2 | |
| 16 | 40 | |
| 17 | Zero-shot translation for indian languages with sparse data | 3 |
| 18 | 1 | |
| 19 | ProbLog2: From probabilistic programming to statistical relational learning | 5 |
| 20 | Data acquisition and modeling for learning and reasoning in probabilistic logic environment | 0 |
About Dimitar Shterionov
Dimitar Shterionov is a scholar working on Human-Computer Interaction, Artificial Intelligence and Developmental and Educational Psychology, having authored 27 papers that have together received 202 indexed citations. Recurring topics across this work include Natural Language Processing Techniques (15 papers), Topic Modeling (12 papers) and Hand Gesture Recognition Systems (5 papers). The work is most often cited by research in Human-Computer Interaction (36 citations), Artificial Intelligence (157 citations) and Health Informatics (4 citations). Dimitar Shterionov has collaborated with scholars based in Netherlands, Ireland and Belgium. Frequent co-authors include Andy Way, Eva Vanmassenhove, Alberto Poncelas, Chris Emmery, Peyman Passban, Declan Groves, Joss Moorkens, Joachim Wagner, Annelies Braffort and Cristina España-Bonet. Their work appears in journals such as Information, Universal Access in the Information Society and Machine Translation.
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.