Mateusz Ujma

470 citations
4 papers · 74 · h-index 3

Impact in

  • Software top 10%
    • Software Testing and Debugging Techniques
    • Software Reliability and Analysis Research
    • Advanced Software Engineering Methodologies

Papers in

Mateusz Ujma

3 papers receiving 74 citations

Peers

Mateusz Ujma
Comparison fields: 5 of 19
  • Software 30
  • Artificial Intelligence 46
  • Computer Networks and Communications 29
  • Information Systems 27
  • Computational Theory and Mathematics 15
Replace Markus Dahlweid with:
Markus Dahlweid Germany
Maik Merten Germany
Marc Pantel France
Antti E. J. Hyvärinen Switzerland
Therese Berg Sweden
Johannes Oetsch Austria
Fabrice Bouquet France
Philippe Dhaussy France
Roberto Vigo Denmark
Aleksandar Chakarov United States
Mateusz Ujma relative to Markus Dahlweid Germany Markus Dahlweid's profile →
Citations per field
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Markus Dahlweid · 1×
Citations per year

Countries citing papers authored by Mateusz Ujma

Since Specialization
Citations

This map shows the geographic impact of Mateusz Ujma'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 Mateusz Ujma with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mateusz Ujma more than expected).

Fields of papers citing papers by Mateusz Ujma

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mateusz Ujma. 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 Mateusz Ujma. The network helps show where Mateusz Ujma may publish in the future.

Co-authors

The 21 scholars most cited alongside Mateusz Ujma, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Mateusz Ujma Line = papers co-authored together Mateusz Ujma links everyone, so they are left out of the graph.

All Works

4 of 4 papers shown

About Mateusz Ujma

Mateusz Ujma is a scholar working on Computational Theory and Mathematics, Artificial Intelligence, Software, Computer Networks and Communications and Hardware and Architecture, having authored 4 papers that have together received 74 indexed citations. Recurring topics across this work include Formal Methods in Verification (3 papers), Software Reliability and Analysis Research (2 papers), Advanced Software Engineering Methodologies (2 papers), Software System Performance and Reliability (1 paper), Real-Time Systems Scheduling (1 paper) and Software Testing and Debugging Techniques (1 paper). The work is most often cited by research in Software (30 citations), Artificial Intelligence (46 citations), Computer Networks and Communications (29 citations), Information Systems (27 citations) and Computational Theory and Mathematics (15 citations). Mateusz Ujma has collaborated with scholars based in United Kingdom, United States and Sweden. Frequent co-authors include Oksana Tkachuk, Peter Mehlitz, Pooyan Jamshidi, Nicolás D’Ippolito, Stepan Shevtsov, Thomas Vogel, Henry Hoffmann, Martina Maggio, Antonio Filieri and Amir Molzam Sharifloo. Their work appears in journals such as ACM Transactions on Autonomous and Adaptive Systems, Logical Methods in Computer Science, EPiC series in computing and Oxford University Research Archive (ORA) (University of Oxford).

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.

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