Igor Pak

176 papers receiving 2.0k citations

Peers

Igor Pak
Comparison fields: 5 of 82
  • Discrete Mathematics and Combinatorics 880
  • Algebra and Number Theory 380
  • Geometry and Topology 487
  • Spectroscopy 622
  • Mathematical Physics 335
Replace Philippe Di Francesco with:
Philippe Di Francesco France
Walter Van Assche Belgium
M. L. Mehta France
Mourad E. H. Ismail United States
Alexander Varchenko United States
А. П. Веселов Russia
A. U. Klimyk Ukraine
Mark Adler United States
Audrey Terras United States
Etsurō Date Japan
Igor Pak relative to Philippe Di Francesco France Philippe Di Francesco's profile →
Citations per field
00.5×4.8×
Philippe Di Francesco · 1×
Citations per year

Countries citing papers authored by Igor Pak

Since Specialization
Citations

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

Fields of papers citing papers by Igor Pak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Igor Pak, 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 Igor Pak Line = papers co-authored together Igor Pak links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 189 papers — load more, or switch the sort, to bring in the rest.

#Work
1 199975
2 200675
3 199867
4 201458
5 200157
6 200043
7 200241
8 200138
9 200037
10 199637
11 200036
12 199436
13 200935
14 200435
15 199833
16 200032
17 199932
18 200431
19 200730
20 199829

About Igor Pak

Igor Pak is a scholar working on Discrete Mathematics and Combinatorics, Computational Theory and Mathematics, Geometry and Topology, Spectroscopy and Mathematical Physics, having authored 189 papers that have together received 2.2k indexed citations. Recurring topics across this work include Advanced Combinatorial Mathematics (76 papers), Spectroscopy and Laser Applications (34 papers), Advanced Mathematical Identities (24 papers), Molecular Spectroscopy and Structure (23 papers), Advanced Chemical Physics Studies (21 papers), Limits and Structures in Graph Theory (21 papers), graph theory and CDMA systems (20 papers) and Computational Geometry and Mesh Generation (19 papers). The work is most often cited by research in Discrete Mathematics and Combinatorics (880 citations), Algebra and Number Theory (380 citations), Geometry and Topology (487 citations), Spectroscopy (622 citations) and Mathematical Physics (335 citations). Igor Pak has collaborated with scholars based in United States, Germany and Russia. Frequent co-authors include G. Winnewisser, Greta Panova, Daniel Roth, Л. А. Сурин, Frank Lewen, Martin Hepp, Б. С. Думеш, Ernesto Vallejo, László Lovász and Alexander Lubotzky. Their work appears in journals such as Journal of Combinatorial Theory Series A, Journal of Molecular Spectroscopy, Discrete & Computational Geometry, The Journal of Chemical Physics and European Journal of Combinatorics.

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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