Alexei Sharpanskykh

118 papers receiving 1.1k citations

Peers

Alexei Sharpanskykh
Comparison fields: 5 of 107
  • Management Information Systems 241
  • Radiological and Ultrasound Technology 114
  • Statistics, Probability and Uncertainty 116
  • Management Science and Operations Research 162
  • Transportation 79
Replace Dilip A. Patel with:
Dilip A. Patel United Kingdom
Andreas Gregoriades Cyprus
Ren‐Jye Dzeng Taiwan
B. L. William Wong United Kingdom
M. Birna van Riemsdijk Netherlands
Ling Rothrock United States
Dongping Cao China
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Citations per year

Countries citing papers authored by Alexei Sharpanskykh

Since Specialization
Citations

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

Fields of papers citing papers by Alexei Sharpanskykh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 128 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2009148
2 2009123
3 200665
4 201139
5 201433
6 201131
7 201027
8 200626
9 201125
10 201925
11 201820
12 202119
13
Formal Modeling and Analysis of Organizations
200518
14 201917
15 201916
16 201116
17 200715
18 201915
19 202014
20 200814

About Alexei Sharpanskykh

Alexei Sharpanskykh is a scholar working on Radiological and Ultrasound Technology, Management Information Systems, Management Science and Operations Research, Artificial Intelligence and Statistics, Probability and Uncertainty, having authored 128 papers that have together received 1.2k indexed citations. Recurring topics across this work include Multi-Agent Systems and Negotiation (28 papers), Occupational Health and Safety Research (22 papers), Evacuation and Crowd Dynamics (20 papers), Business Process Modeling and Analysis (19 papers), Human-Automation Interaction and Safety (18 papers), Complex Systems and Decision Making (15 papers), Risk and Safety Analysis (15 papers) and Air Traffic Management and Optimization (14 papers). The work is most often cited by research in Management Information Systems (241 citations), Radiological and Ultrasound Technology (114 citations), Statistics, Probability and Uncertainty (116 citations), Management Science and Operations Research (162 citations) and Transportation (79 citations). Alexei Sharpanskykh has collaborated with scholars based in Netherlands, United Kingdom and Canada. Frequent co-authors include Jan Treur, Viara Popova, Catholijn M. Jonker, Tibor Bosse, Lourens van der Meij, Sybert Stroeve, Richard Curran, Kashif Zia, H.A.P. Blom and Pınar Yolum. Their work appears in journals such as Applied Intelligence, Lecture notes in computer science, Computational and Mathematical Organization Theory, Reliability Engineering & System Safety and Transportation Research Part C Emerging Technologies.

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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