Irina Subbotina

1.2k total citations · 1 hit paper
21 papers, 918 citations indexed

About

Irina Subbotina is a scholar working on Environmental Engineering, Artificial Intelligence and Global and Planetary Change. According to data from OpenAlex, Irina Subbotina has authored 21 papers receiving a total of 918 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Environmental Engineering, 9 papers in Artificial Intelligence and 9 papers in Global and Planetary Change. Recurrent topics in Irina Subbotina's work include Atmospheric and Environmental Gas Dynamics (9 papers), Geochemistry and Geologic Mapping (9 papers) and Soil Geostatistics and Mapping (8 papers). Irina Subbotina is often cited by papers focused on Atmospheric and Environmental Gas Dynamics (9 papers), Geochemistry and Geologic Mapping (9 papers) and Soil Geostatistics and Mapping (8 papers). Irina Subbotina collaborates with scholars based in Russia, Bulgaria and Germany. Irina Subbotina's co-authors include Yakov Kuzyakov, Haiqing Chen, И. Н. Богомолова, Xingliang Xu, Martin Werth, Alexander Sergeev, Alexander Buevich, O. Lvova, Alexander Medvedev and Alexandra I. Kosachenko and has published in prestigious journals such as Soil Biology and Biochemistry, Atmospheric Environment and Atmospheric Pollution Research.

In The Last Decade

Irina Subbotina

14 papers receiving 890 citations

Hit Papers

align trajectories sort by overperformance

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Black carbon decomposition and incorporation into soil microbial biomass estimated by 14C labeling

2008 852 citations Yakov Kuzyakov, Irina Subbotina et al. Soil Biology and Biochemistry profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Irina Subbotina Russia	5	659	244	174	160	134	21	918
Shuaidong Hu China	8	608 0.9×	141 0.6×	181 1.0×	188 1.2×	114 0.9×	8	894
Thi Thu Nhan Nguyen Australia	10	569 0.9×	182 0.7×	130 0.7×	111 0.7×	102 0.8×	11	869
Roberto Calvelo Pereira New Zealand	18	501 0.8×	146 0.6×	109 0.6×	192 1.2×	260 1.9×	30	1.1k
Alfred Obia Norway	10	755 1.1×	237 1.0×	279 1.6×	75 0.5×	102 0.8×	22	1.0k
Natalia Rogovska United States	11	526 0.8×	147 0.6×	160 0.9×	85 0.5×	103 0.8×	24	869
Ziwen Lin China	9	470 0.7×	107 0.4×	113 0.6×	129 0.8×	110 0.8×	12	729
Mehran Rezaei Rashti Australia	18	662 1.0×	141 0.6×	114 0.7×	268 1.7×	186 1.4×	56	1.3k
H. M. S. K. Herath Sri Lanka	12	713 1.1×	271 1.1×	313 1.8×	101 0.6×	259 1.9×	21	1.2k
Xinliang Dong China	13	456 0.7×	150 0.6×	148 0.9×	90 0.6×	103 0.8×	25	703
Arezoo Taghizadeh‐Toosi Denmark	17	915 1.4×	201 0.8×	178 1.0×	307 1.9×	134 1.0×	31	1.4k

Countries citing papers authored by Irina Subbotina

Since Specialization

Citations

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

Fields of papers citing papers by Irina Subbotina

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Irina Subbotina

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

All Works

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20 of 20 papers shown

Buevich, Alexander, et al.. (2023). A hybrid model based on an artificial neural network with a long chain of short-term memory elements and a discrete wavelet transform for predicting surface methane content in the Arctic area. Arctic Ecology and Economy. 13(3). 428–436.

Sergeev, Alexander, et al.. (2023). Hybrid model combining LSTM with discrete wavelet transformation to predict surface methane concentration in the Arctic Island Belyy. Atmospheric Environment. 317. 120210–120210. 6 indexed citations

Sergeev, Alexander, et al.. (2022). Comparing the types of artificial neural networks to predict the carbon dioxide concentration changes. AIP conference proceedings. 2425. 110007–110007.

Sergeev, Alexander, et al.. (2022). Improved algorithm for splitting raw data into training and test subsamples for MLP-based models. AIP conference proceedings. 2425. 110009–110009. 1 indexed citations

Subbotina, Irina, et al.. (2020). Two-step combined algorithm for improving the accuracy of predicting methane concentration in atmospheric air based on the NARX neural network and subsequent prediction of residuals. Arctic Ecology and Economy. 59–67. 1 indexed citations

Medvedev, Alexander, et al.. (2020). The forecast of the methane concentration changes for the different time periods on the Arctic island Bely. AIP conference proceedings. 2293. 120019–120019. 1 indexed citations

Sergeev, Alexander, et al.. (2020). Prediction the dynamic of changes in the concentrations of main greenhouse gases by an artificial neural network type NARX. AIP conference proceedings. 2293. 120020–120020. 2 indexed citations

Subbotina, Irina, et al.. (2019). DISPERSE COMPOSITION OF THE DUST IN THE GROUND LAYER OF THE URBANIZED AREA ATMOSPHERE ACCORDING TO THE DATA OF ECOLOGICAL SCREENING ON THE EXAMPLE OF YEKATERINBURG CITY.

Buevich, Alexander, et al.. (2019). Statistical characteristics calculation of the natural dust size distribution in the air surface layer of Belyy Island. AIP conference proceedings. 2186. 50012–50012. 1 indexed citations

10.

Sergeev, Alexander, et al.. (2019). Particulate matter size distribution in air surface layer of Middle Ural and Arctic territories. Atmospheric Pollution Research. 10(4). 1220–1226. 4 indexed citations

11.

Buevich, Alexander, et al.. (2019). Prediction of the chrome distribution in subarctic Noyabrsk using co-kriging, generalized regression neural network, multilayer perceptron, and hybrid technics. 77–86.

12.

Buevich, Alexander, et al.. (2018). Forecasting of spatial variable by the models based on artificial neural networks on an example of heavy metal content in topsoil. AIP conference proceedings. 2040. 50007–50007. 2 indexed citations

13.

Subbotina, Irina, et al.. (2018). Statistical analysis of the spatial distribution of impurities in the snow cover in the vicinity of copper mine in the Middle Ural of Russia. AIP conference proceedings. 2048. 60012–60012.

14.

Subbotina, Irina, et al.. (2018). DISPERSE COMPOSITION OF THE DUST IN THE GROUND LAYER OF THE URBANIZED AREA ATMOSPHERE ACCORDING TO THE DATA OF ECOLOGICAL SCREENING ON THE EXAMPLE OF EKATERINBURG CITY.

15.

Subbotina, Irina, et al.. (2018). Multilayer perceptron, generalized regression neural network, and hybrid model in predicting the spatial distribution of impurity in the topsoil of urbanized area. AIP conference proceedings. 1982. 20004–20004. 3 indexed citations

16.

Buevich, Alexander, et al.. (2018). Chromium distribution forecasting using multilayer perceptron neural network and multilayer perceptron residual kriging. AIP conference proceedings. 1978. 440019–440019. 4 indexed citations

17.

Buevich, Alexander, et al.. (2018). Training algorithms for artificial neural network in predicting of the content of chemical elements in the upper soil layer. AIP conference proceedings. 11 indexed citations

18.

Sergeev, Alexander, et al.. (2017). High variation subarctic topsoil pollutant concentration prediction using neural network residual kriging. AIP conference proceedings. 1836. 20023–20023. 3 indexed citations

19.

Kuzyakov, Yakov, Irina Subbotina, Haiqing Chen, И. Н. Богомолова, & Xingliang Xu. (2008). Black carbon decomposition and incorporation into soil microbial biomass estimated by 14C labeling. Soil Biology and Biochemistry. 41(2). 210–219. 852 indexed citations breakdown →

20.

Werth, Martin, Irina Subbotina, & Yakov Kuzyakov. (2006). Three-source partitioning of CO2 efflux from soil planted with maize by 13C natural abundance fails due to inactive microbial biomass. Soil Biology and Biochemistry. 38(9). 2772–2781. 26 indexed citations

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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