Maxim Bakaev

557 citations
53 papers · 228 · h-index 8

Impact in

Papers in

Maxim Bakaev

43 papers receiving 206 citations

Peers

Maxim Bakaev
Comparison fields: 5 of 68
  • Human-Computer Interaction 108
  • Developmental and Educational Psychology 48
  • Computer Vision and Pattern Recognition 64
  • Information Systems 35
  • Information Systems and Management 9
Replace Luis Quesada with:
Luis Quesada Costa Rica
Valéria Farinazzo Martins Brazil
Achraf Othman Qatar
Katsuko T. Nakahira Japan
Yoshimi Fukumura Japan
Rafael Duque Spain
Mahmood Jasim United States
Maximiliano Paredes Velasco Spain
Norizan Mat Diah Malaysia
Richard Borovoy United States
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Citations per field
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Citations per year

Countries citing papers authored by Maxim Bakaev

Since Specialization
Citations

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

Fields of papers citing papers by Maxim Bakaev

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 16 scholars most cited alongside Maxim Bakaev, 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 Maxim Bakaev Line = papers co-authored together Maxim Bakaev links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 53 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202342
2 202235
3 201912
4 201611
5 200810
6 20238
7 20137
8 20157
9 20087
10 20106
11 20166
12 20215
13 20235
14 20195
15 20214
16
Kansei Engineering Experimental Research with University Websites
20164
17 20174
18 20203
19 20233
20 20223

About Maxim Bakaev

Maxim Bakaev is a scholar working on Information Systems, Human-Computer Interaction, Sociology and Political Science, Social Psychology and Computer Vision and Pattern Recognition, having authored 53 papers that have together received 228 indexed citations. Recurring topics across this work include Color perception and design (6 papers), Interactive and Immersive Displays (5 papers), Web Data Mining and Analysis (5 papers), Web Applications and Data Management (4 papers), Multimedia Communication and Technology (4 papers), Hand Gesture Recognition Systems (4 papers), Technology Use by Older Adults (4 papers) and Socioeconomic and Demographic Analysis (3 papers). The work is most often cited by research in Human-Computer Interaction (108 citations), Developmental and Educational Psychology (48 citations), Computer Vision and Pattern Recognition (64 citations), Information Systems (35 citations) and Information Systems and Management (9 citations). Maxim Bakaev has collaborated with scholars based in Russia, Germany and India. Frequent co-authors include Martin Gaedke, Tatiana Avdeenko, R Elakkiya, Ketan Kotecha, V. Subramaniyaswamy, О. М. Разумникова, Sebastian Heil, Lubna A. Gabralla, Ajith Abraham and Jatinderkumar R. Saini. Their work appears in journals such as IT Professional, Big Data and Cognitive Computing, Future Internet, Journal of Intelligence and International Journal of Mental Health Nursing.

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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