Henrik Björklund

30 papers receiving 216 citations

Peers

Henrik Björklund
Comparison fields: 5 of 45
  • Artificial Intelligence 161
  • Computational Theory and Mathematics 132
  • Computer Networks and Communications 60
  • Management Science and Operations Research 32
  • Signal Processing 23
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Justin Hsu United States
Martin Mundhenk Germany
Wouter Gelade Belgium
Sergei Vorobyov Germany
Pietro Sala Italy
Chiaki Sakama Japan
Tanel Tammet Estonia
Brandon Moore United States
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Citations per field
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Citations per year

Countries citing papers authored by Henrik Björklund

Since Specialization
Citations

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

Fields of papers citing papers by Henrik Björklund

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Henrik Björklund

This figure shows the co-authorship network connecting the top 25 collaborators of Henrik Björklund. A scholar is included among the top collaborators of Henrik Björklund 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 Henrik Björklund. Henrik Björklund is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
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2 1
3 0
4
Predicting User Competence from Linguistic Data
2
5
Single-Rooted DAGs in Regular DAG Languages: Parikh Image and Path Languages
0
6 7
7 2
8
On the Parameterized Complexity of Linear Context-Free Rewriting Systems
2
9
A note on the complexity of deterministic tree-walking transducers
1
10 2
11 13
12 20
13 6
14 24
15 42
16 15
17
Combinatorial Optimization for Infinite Games on Graphs
1
18
Randomized Subexponential Algorithms for Infinite Games
5
19 21
20
An Experimental Study of Algorithms for Completely Unimodal Optimization
2

About Henrik Björklund

Henrik Björklund is a scholar working on Computational Theory and Mathematics, Artificial Intelligence and Numerical Analysis, having authored 38 papers that have together received 247 indexed citations. Recurring topics across this work include semigroups and automata theory (10 papers), Artificial Intelligence in Games (8 papers) and Natural Language Processing Techniques (7 papers). The work is most often cited by research in Computational Theory and Mathematics (132 citations), Artificial Intelligence (161 citations) and Software (11 citations). Henrik Björklund has collaborated with scholars based in Sweden, Germany and Belgium. Frequent co-authors include Sergei Vorobyov, Wim Martens, Thomas Schwentick, Sven Sandberg, Wouter Gelade, Ola Svensson, Frank Drewes, Suna Bensch, Olle Nilsson and Martin Berglund. Their work appears in journals such as Theoretical Computer Science, Journal of Computer and System Sciences and ACM Transactions on Database Systems.

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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