Bogdan Bochenek

20 papers receiving 392 citations

Hit Papers

Machine Learning in Weather Prediction and Climate Analys...2022202620232024202250100150

Peers

Bogdan Bochenek
Comparison fields: 5 of 80
  • Atmospheric Science 163
  • Global and Planetary Change 153
  • Environmental Engineering 122
  • Electrical and Electronic Engineering 86
  • Artificial Intelligence 61
Replace Shihao Wang with:
Shihao Wang China
Felix Kleinert Germany
Scarlet Stadtler Germany
Lukas Hubert Leufen Germany
Clara Betancourt Germany
Shrutilipi Bhattacharjee India
Kostas Philippopoulos Greece
Adam Jaczewski Poland
Fadhilah Yusof Malaysia
Claudia Gutiérrez Spain
Bogdan Bochenek relative to Shihao Wang China Shihao Wang's profile →
Citations per field
00.5×4.3×
Shihao Wang · 1×
Citations per year

Countries citing papers authored by Bogdan Bochenek

Since Specialization
Citations

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

Fields of papers citing papers by Bogdan Bochenek

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bogdan Bochenek

This figure shows the co-authorship network connecting the top 25 collaborators of Bogdan Bochenek. A scholar is included among the top collaborators of Bogdan Bochenek 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 Bogdan Bochenek. Bogdan Bochenek is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 2
2 0
3 0
4 6
5 0
6 0
7 4
8 2
9 5
10 5
11 11
12
Machine Learning in Weather Prediction and Climate Analyses—Applications and Perspectivesbreakdown →
152
13 5
14 26
15 6
16 38
17 19
18 18
19 35
20 10

About Bogdan Bochenek

Bogdan Bochenek is a scholar working on Atmospheric Science, Global and Planetary Change and Modeling and Simulation, having authored 24 papers that have together received 405 indexed citations. Recurring topics across this work include Meteorological Phenomena and Simulations (7 papers), Climate variability and models (7 papers) and Air Quality and Health Impacts (5 papers). The work is most often cited by research in Atmospheric Science (163 citations), Environmental Engineering (122 citations) and Global and Planetary Change (153 citations). Bogdan Bochenek has collaborated with scholars based in Poland, Germany and South Africa. Frequent co-authors include Zbigniew Ustrnul, Agnieszka Wypych, Anita Bokwa, Mirosław Zimnoch, Agnieszka Sulikowska, Frank‐M. Chmielewski, Adam Jaczewski, Mariusz Figurski, Jakub Jurasz and Marcin Wdowikowski. Their work appears in journals such as Scientific Reports, European Heart Journal and Energy Conversion and Management.

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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