Maksim Kitsak
- Statistical and Nonlinear Physics top 0.1%
- Molecular Biology top 10%
- Computer Networks and Communications top 2%
- Artificial Intelligence top 2%
- Computational Theory and Mathematics top 1%
- Co-authors
- H. Eugene StanleyShlomo HavlinFredrik LiljerosLev MuchnikHernán A. MakseLazaros K. GallosDmitri KrioukovMarián Boguñá
- Topics
- Complex Network Analysis Techniques (17 papers)Opinion Dynamics and Social Influence (8 papers)Bioinformatics and Genomic Networks (5 papers)
- Journals
- NatureScienceNature Communications
- Partner nations
- United StatesNetherlandsSpain
In The Last Decade
Maksim Kitsak
29 papers receiving 4.8k citations
Hit Papers
Peers
Comparison fields: 5 of 183
- Statistical and Nonlinear Physics 2.7k
- Molecular Biology 1.2k
- Computer Networks and Communications 608
- Artificial Intelligence 599
- Computational Theory and Mathematics 593
Countries citing papers authored by Maksim Kitsak
This map shows the geographic impact of Maksim Kitsak'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 Maksim Kitsak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Maksim Kitsak more than expected).
Fields of papers citing papers by Maksim Kitsak
This network shows the impact of papers produced by Maksim Kitsak. 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 Maksim Kitsak. The network helps show where Maksim Kitsak may publish in the future.
Co-authorship network of co-authors of Maksim Kitsak
This figure shows the co-authorship network connecting the top 25 collaborators of Maksim Kitsak. A scholar is included among the top collaborators of Maksim Kitsak 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 Maksim Kitsak. Maksim Kitsak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 8 | |
| 6 | 4 | |
| 7 | 10 | |
| 8 | 30 | |
| 9 | 31 | |
| 10 | 48 | |
| 11 | 20 | |
| 12 | 70 | |
| 13 | 6 | |
| 14 | Popularity versus similarity in growing networks | 1 |
| 15 | 68 | |
| 16 | Why hubs may not be the most efficient spreaders | 1 |
| 17 | Identifying influential spreaders in complex networks | 47 |
| 18 | Hyperbolic geometry of complex networksbreakdown → | 544 |
| 19 | 23 | |
| 20 | 49 |
About Maksim Kitsak
Maksim Kitsak is a scholar working on Statistical and Nonlinear Physics, Modeling and Simulation and Mathematical Physics, having authored 34 papers that have together received 5.0k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (17 papers), Opinion Dynamics and Social Influence (8 papers) and Bioinformatics and Genomic Networks (5 papers). The work is most often cited by research in Statistical and Nonlinear Physics (2.7k citations), Computational Theory and Mathematics (593 citations) and Transportation (250 citations). Maksim Kitsak has collaborated with scholars based in United States, Netherlands and Spain. Frequent co-authors include H. Eugene Stanley, Shlomo Havlin, Fredrik Liljeros, Lev Muchnik, Hernán A. Makse, Lazaros K. Gallos, Dmitri Krioukov, Marián Boguñá, Fragkiskos Papadopoulos and Jörg Menche. Their work appears in journals such as Nature, Science and Nature Communications.
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.