Szymon Bobek
- Artificial Intelligence top 10%
- Computer Vision and Pattern Recognition top 10%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Experimental and Cognitive Psychology
- Co-authors
- Grzegorz J. NalepaKrzysztof KuttKrzysztof KluzaSławomir TadejaLala RajaoarisoaTimoleon KipourosJacek TaborŁukasz Struski
- Topics
- Context-Aware Activity Recognition Systems (13 papers)Explainable Artificial Intelligence (XAI) (6 papers)Data Stream Mining Techniques (5 papers)
- Cited by
- Health InformaticsExperimental and Cognitive PsychologyComputer Vision and Pattern Recognition
- Journals
- IEEE AccessSensorsInformation Fusion
In The Last Decade
Szymon Bobek
37 papers receiving 344 citations
Peers
Comparison fields: 5 of 68
- Artificial Intelligence 143
- Computer Vision and Pattern Recognition 91
- Computer Networks and Communications 68
- Information Systems 67
- Experimental and Cognitive Psychology 59
Countries citing papers authored by Szymon Bobek
This map shows the geographic impact of Szymon Bobek'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 Szymon Bobek with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Szymon Bobek more than expected).
Fields of papers citing papers by Szymon Bobek
This network shows the impact of papers produced by Szymon Bobek. 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 Szymon Bobek. The network helps show where Szymon Bobek may publish in the future.
Co-authorship network of co-authors of Szymon Bobek
This figure shows the co-authorship network connecting the top 25 collaborators of Szymon Bobek. A scholar is included among the top collaborators of Szymon Bobek 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 Szymon Bobek. Szymon Bobek 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 | 2 | |
| 3 | 3 | |
| 4 | 3 | |
| 5 | 5 | |
| 6 | 14 | |
| 7 | 5 | |
| 8 | 9 | |
| 9 | 9 | |
| 10 | 6 | |
| 11 | 1 | |
| 12 | 8 | |
| 13 | 31 | |
| 14 | Improving indoor localization by user feedback | 8 |
| 15 | 10 | |
| 16 | 6 | |
| 17 | Learning sensors usage patterns in mobile context-aware systems | 4 |
| 18 | Overview of Recommendation Techniques in Business Process Modeling. | 16 |
| 19 | HeaRT rule inference engine in intelligent systems | 1 |
| 20 | Overview of rule inference algorithms for structured rule bases | 1 |
About Szymon Bobek
Szymon Bobek is a scholar working on Signal Processing, Computer Vision and Pattern Recognition and Artificial Intelligence, having authored 38 papers that have together received 352 indexed citations. Recurring topics across this work include Context-Aware Activity Recognition Systems (13 papers), Explainable Artificial Intelligence (XAI) (6 papers) and Data Stream Mining Techniques (5 papers). The work is most often cited by research in Health Informatics (10 citations), Experimental and Cognitive Psychology (59 citations) and Computer Vision and Pattern Recognition (91 citations). Szymon Bobek has collaborated with scholars based in Poland, Germany and Belgium. Frequent co-authors include Grzegorz J. Nalepa, Krzysztof Kutt, Krzysztof Kluza, Sławomir Tadeja, Lala Rajaoarisoa, Timoleon Kipouros, Jacek Tabor, Łukasz Struski, Moamar Sayed‐Mouchaweh and Marcin Grzegorzek. Their work appears in journals such as IEEE Access, Sensors and Information Fusion.
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.