Pavol Bielik
- Information Systems top 2%
- Software top 2%
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Signal Processing top 5%
- Co-authors
- Martin VechevVeselin RaychevAndreas KrauseLaurent VanbeverMichal BarlaMária BielikováMislav BalunovićMarc Fischer
- Topics
- Software Engineering Research (9 papers)Software Testing and Debugging Techniques (6 papers)Machine Learning and Data Classification (5 papers)
- Journals
- ACM SIGPLAN NoticesProceedings of the ACM on Programming LanguagesRepository for Publications and Research Data (ETH Zurich)
- Partner nations
- SwitzerlandSlovakiaGermany
In The Last Decade
Pavol Bielik
20 papers receiving 464 citations
Peers
Comparison fields: 5 of 47
- Information Systems 278
- Software 204
- Artificial Intelligence 170
- Computer Networks and Communications 150
- Signal Processing 118
Countries citing papers authored by Pavol Bielik
This map shows the geographic impact of Pavol Bielik'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 Pavol Bielik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Pavol Bielik more than expected).
Fields of papers citing papers by Pavol Bielik
This network shows the impact of papers produced by Pavol Bielik. 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 Pavol Bielik. The network helps show where Pavol Bielik may publish in the future.
Co-authorship network of co-authors of Pavol Bielik
This figure shows the co-authorship network connecting the top 25 collaborators of Pavol Bielik. A scholar is included among the top collaborators of Pavol Bielik 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 Pavol Bielik. Pavol Bielik is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 4 | |
| 3 | 2 | |
| 4 | 1 | |
| 5 | Learning to Solve SMT Formulas | 14 |
| 6 | 12 | |
| 7 | Program Synthesis for Character Level Language Modeling | 8 |
| 8 | PHOG: probabilistic model for code | 55 |
| 9 | 77 | |
| 10 | 22 | |
| 11 | 72 | |
| 12 | 24 | |
| 13 | 7 | |
| 14 | 49 | |
| 15 | 55 | |
| 16 | 8 | |
| 17 | 8 | |
| 18 | 20 | |
| 19 | 44 | |
| 20 | 10 |
About Pavol Bielik
Pavol Bielik is a scholar working on Software, Information Systems and Signal Processing, having authored 20 papers that have together received 494 indexed citations. Recurring topics across this work include Software Engineering Research (9 papers), Software Testing and Debugging Techniques (6 papers) and Machine Learning and Data Classification (5 papers). The work is most often cited by research in Software (204 citations), Information Systems (278 citations) and Signal Processing (118 citations). Pavol Bielik has collaborated with scholars based in Switzerland, Slovakia and Germany. Frequent co-authors include Martin Vechev, Veselin Raychev, Andreas Krause, Laurent Vanbever, Michal Barla, Mária Bieliková, Mislav Balunović, Marc Fischer, Gagandeep Singh and Igor Linkov. Their work appears in journals such as ACM SIGPLAN Notices, Proceedings of the ACM on Programming Languages and Repository for Publications and Research Data (ETH Zurich).
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.