Raghav Kulkarni

27 papers receiving 198 citations

Peers

Raghav Kulkarni
Comparison fields: 5 of 34
  • Information Systems 108
  • Artificial Intelligence 91
  • Computational Theory and Mathematics 85
  • Computer Networks and Communications 64
  • Management Information Systems 18
Replace Jan Óbdržálek with:
Jan Óbdržálek Czechia
Jason Teutsch United States
Sebastian Ordyniak Austria
Ernst–Erich Doberkat Germany
Jean-Marc Vincent France
Gwendolyn H. Walton United States
Paolo Felli Italy
Salvador Roura Spain
Mohona Ghosh India
Roger Villemaire Canada
Raghav Kulkarni relative to Jan Óbdržálek Czechia Jan Óbdržálek's profile →
Citations per field
00.5×4.5×
Jan Óbdržálek · 1×
Citations per year

Countries citing papers authored by Raghav Kulkarni

Since Specialization
Citations

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

Fields of papers citing papers by Raghav Kulkarni

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raghav Kulkarni

This figure shows the co-authorship network connecting the top 25 collaborators of Raghav Kulkarni. A scholar is included among the top collaborators of Raghav Kulkarni 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 Raghav Kulkarni. Raghav Kulkarni 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
1 0
2
CrystalBall: Gazing in the Black Box of SAT Solving.
4
3 4
4 1
5 3
6 6
7 1
8 0
9
On Fractional Block Sensitivity.
1
10
Space complexity: what makes planar graphs special?
1
11
Query complexity of matroids.
2
12
15
13 7
14 0
15
Perfect Matching in Bipartite Planar Graphs is in UL.
1
16
Some perfect matchings and perfect half-integral matchings in NC ∗
5
17
Parity Problems in Planar Graphs.
2
18 6
19
Quantum Query Complexity in Computational Geometry
1
20 1

About Raghav Kulkarni

Raghav Kulkarni is a scholar working on Computational Theory and Mathematics, Discrete Mathematics and Combinatorics and Computer Graphics and Computer-Aided Design, having authored 30 papers that have together received 211 indexed citations. Recurring topics across this work include Complexity and Algorithms in Graphs (20 papers), Advanced Graph Theory Research (15 papers) and Optimization and Search Problems (6 papers). The work is most often cited by research in Computational Theory and Mathematics (85 citations), Information Systems (108 citations) and Discrete Mathematics and Combinatorics (11 citations). Raghav Kulkarni has collaborated with scholars based in India, Singapore and United States. Frequent co-authors include Jason Teutsch, Prateek Saxena, Loi Luu, Samir Datta, Sambuddha Roy, Meena Mahajan, Mark Braverman, Avishay Tal, Sourav Chakraborty and Miklós Sántha. Their work appears in journals such as Theoretical Computer Science, Journal of Computer and System Sciences and Lecture notes in computer science.

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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