Danil Kirsanov

5 papers receiving 408 citations

Hit Papers

Fast exact and approximate geodesics on meshes20052026201220192005100200300

Peers

Danil Kirsanov
Comparison fields: 5 of 66
  • Computational Mechanics 283
  • Computer Graphics and Computer-Aided Design 247
  • Computer Vision and Pattern Recognition 163
  • Aerospace Engineering 33
  • Control and Systems Engineering 24
Replace Tatiana Surazhsky with:
Tatiana Surazhsky Israel
Pushkar Joshi United States
Pierre E. Bézier France
Henry N. Christiansen United States
Soji Yamakawa United States
Olga Diamanti United States
David R. Forsey Canada
Noam Aigerman United States
François Labelle United States
Yair Kurzion United States
Danil Kirsanov relative to Tatiana Surazhsky Israel Tatiana Surazhsky's profile →
Citations per field
00.5×1.5×
Tatiana Surazhsky · 1×
Citations per year

Countries citing papers authored by Danil Kirsanov

Since Specialization
Citations

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

Fields of papers citing papers by Danil Kirsanov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Danil Kirsanov

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

All Works

6 of 6 papers shown
#WorkIndexed citations
1 0
2
Fast exact and approximate geodesics on meshesbreakdown →
348
3 56
4 20
5
Minimal discrete curves and surfaces
9
6 1

About Danil Kirsanov

Danil Kirsanov is a scholar working on Computer Graphics and Computer-Aided Design, Signal Processing and Computational Mechanics, having authored 6 papers that have together received 434 indexed citations. Recurring topics across this work include Computational Geometry and Mesh Generation (4 papers), Advanced Numerical Analysis Techniques (3 papers) and Data Management and Algorithms (2 papers). The work is most often cited by research in Computer Graphics and Computer-Aided Design (247 citations), Computational Mechanics (283 citations) and Computer Vision and Pattern Recognition (163 citations). Danil Kirsanov has collaborated with scholars based in United States, Norway and United Kingdom. Frequent co-authors include Steven J. Gortler, Tatiana Surazhsky, Hugues Hoppe, Vitaly Surazhsky, Dale Becker, Matteo Cocchini and Steven G. Pytel. Their work appears in journals such as ACM Transactions on Graphics, European Heart Journal Acute Cardiovascular Care and IMAPSource Proceedings.

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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