Martin Bobák
- Artificial Intelligence top 10%
- Computer Networks and Communications top 10%
- Information Systems top 10%
- Computer Vision and Pattern Recognition top 10%
- Signal Processing
- Co-authors
- Viet TranLadislav HluchýÁlvaro López GarcíaIgnacio HerediaGiang NguyenPeter MalíkŠtefan DlugolinskýPeter H. Krammer
- Topics
- Distributed and Parallel Computing Systems (8 papers)Cloud Computing and Resource Management (8 papers)Peer-to-Peer Network Technologies (2 papers)
- Partner nations
- SlovakiaPolandSwitzerland
In The Last Decade
Martin Bobák
17 papers receiving 529 citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Artificial Intelligence 179
- Computer Networks and Communications 86
- Information Systems 78
- Computer Vision and Pattern Recognition 72
- Signal Processing 40
Countries citing papers authored by Martin Bobák
This map shows the geographic impact of Martin Bobák'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 Martin Bobák with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Martin Bobák more than expected).
Fields of papers citing papers by Martin Bobák
This network shows the impact of papers produced by Martin Bobák. 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 Martin Bobák. The network helps show where Martin Bobák may publish in the future.
Co-authorship network of co-authors of Martin Bobák
This figure shows the co-authorship network connecting the top 25 collaborators of Martin Bobák. A scholar is included among the top collaborators of Martin Bobák 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 Martin Bobák. Martin Bobák 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 | 5 | |
| 4 | 0 | |
| 5 | 1 | |
| 6 | 5 | |
| 7 | 1 | |
| 8 | 1 | |
| 9 | 2 | |
| 10 | 4 | |
| 11 | 5 | |
| 12 | 1 | |
| 13 | 0 | |
| 14 | Machine Learning and Deep Learning frameworks and libraries for large-scale data mining: a surveybreakdown → | 516 |
| 15 | 3 | |
| 16 | Application Performance Optimization in Multicloud Environment | 0 |
| 17 | 3 | |
| 18 | 3 | |
| 19 | 1 | |
| 20 | Variants of Genes from the Next Generation Sequencing Data | 1 |
About Martin Bobák
Martin Bobák is a scholar working on Computer Networks and Communications, Information Systems and Information Systems and Management, having authored 21 papers that have together received 555 indexed citations. Recurring topics across this work include Distributed and Parallel Computing Systems (8 papers), Cloud Computing and Resource Management (8 papers) and Peer-to-Peer Network Technologies (2 papers). The work is most often cited by research in Health Informatics (10 citations), Artificial Intelligence (179 citations) and Management Information Systems (37 citations). Martin Bobák has collaborated with scholars based in Slovakia, Poland and Switzerland. Frequent co-authors include Viet Tran, Ladislav Hluchý, Álvaro López García, Ignacio Heredia, Giang Nguyen, Peter Malík, Štefan Dlugolinský, Peter H. Krammer, Mara Graziani and Vincent Andrearczyk. Their work appears in journals such as Artificial Intelligence Review, Computer Science Review and Acta Polytechnica Hungarica.
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.