Igor Griva

1.0k citations
48 papers · 725 indexed · h-index 12

Impact in

Papers in

Igor Griva

46 papers receiving 693 citations

Peers

Igor Griva
Comparison fields: 5 of 123
  • Numerical Analysis 92
  • Electrochemistry 92
  • Computational Theory and Mathematics 96
  • Environmental Engineering 75
  • Electrical and Electronic Engineering 267
Replace Daniel J. Bates with:
Daniel J. Bates United States
Huan Su China
Xing Liu China
Xudong Chen United States
Zuowei Zhang China
Liping Zhang China
Qianxiao Li Singapore
Jae-Hun Jung South Korea
Joel A. Paulson United States
Fei Peng China
Igor Griva relative to Daniel J. Bates United States Daniel J. Bates's profile →
Citations per field
00.5×10×12.5×
Daniel J. Bates · 1×
Citations per year

Countries citing papers authored by Igor Griva

Since Specialization
Citations

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

Fields of papers citing papers by Igor Griva

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown
#Work
1 20221
2 20221
3 20211
4 20193
5 201810
6 201810
7 201713
8 201526
9 20152
10
On the electron transfer through Geobacter sulfurreducens PilA protein Part B Polymer physics
20151
11 20135
12 20110
13 20116
14 20103
15 20106
16 200924
17
Global convergence of a primal-dual interior-point method for nonlinear programming
200816
18 200536
19 20055
20 19987

About Igor Griva

Igor Griva is a scholar working on Numerical Analysis, Electrochemistry, Computational Theory and Mathematics, Electrical and Electronic Engineering and Computational Mechanics, having authored 48 papers that have together received 725 indexed citations. Recurring topics across this work include Molecular Junctions and Nanostructures (11 papers), Advanced Optimization Algorithms Research (9 papers), Electrochemical Analysis and Applications (8 papers), Photosynthetic Processes and Mechanisms (5 papers), Electrochemical sensors and biosensors (4 papers), Microbial Fuel Cells and Bioremediation (4 papers), Sparse and Compressive Sensing Techniques (3 papers) and Iterative Methods for Nonlinear Equations (3 papers). The work is most often cited by research in Numerical Analysis (92 citations), Electrochemistry (92 citations), Computational Theory and Mathematics (96 citations), Environmental Engineering (75 citations) and Electrical and Electronic Engineering (267 citations). Igor Griva has collaborated with scholars based in United States, Kazakhstan and South Korea. Frequent co-authors include Stephen G. Nash, Ariela Sofer, Nikolai Lebedev, Roman A. Polyak, Joel M. Schnur, Scott A. Trammell, Anthony Spano, Stanislav Tsoi, Leonard M. Tender and Anders Blom. Their work appears in journals such as The Journal of Physical Chemistry C, Optimization and Engineering, Atmosphere, Computational Optimization and Applications and Optimization Letters.

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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