Michail Tsagris

181 total papers · 1.4k total citations
49 papers, 714 citations indexed

About

Michail Tsagris is a scholar working on Artificial Intelligence, Statistics and Probability and Environmental Engineering. According to data from OpenAlex, Michail Tsagris has authored 49 papers receiving a total of 714 indexed citations (citations by other indexed papers that have themselves been cited), including 22 papers in Artificial Intelligence, 18 papers in Statistics and Probability and 7 papers in Environmental Engineering. Recurrent topics in Michail Tsagris's work include Advanced Statistical Methods and Models (12 papers), Bayesian Modeling and Causal Inference (8 papers) and Soil Geostatistics and Mapping (7 papers). Michail Tsagris is often cited by papers focused on Advanced Statistical Methods and Models (12 papers), Bayesian Modeling and Causal Inference (8 papers) and Soil Geostatistics and Mapping (7 papers). Michail Tsagris collaborates with scholars based in Greece, United Kingdom and Saudi Arabia. Michail Tsagris's co-authors include Konstantinos C. Fragkos, Christos C. Frangos, Ioannis Tsamardinos, Andrew T. A. Wood, Vincenzo Lagani, Christina Beneki, Hossein Hassani, Nikolaos Pandis, Simon Preston and Alessio Farcomeni and has published in prestigious journals such as SHILAP Revista de lepidopterología, Journal of the American Statistical Association and Bioinformatics.

In The Last Decade

Michail Tsagris

43 papers receiving 698 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Michail Tsagris	191	113	72	57	48	49	714
Ruben H. Zamar	140 0.7×	95 0.8×	204 2.8×	34 0.6×	35 0.7×	30	737
Jie Ding	241 1.3×	149 1.3×	78 1.1×	19 0.3×	18 0.4×	64	850
Manuel J. A. Eugster	247 1.3×	70 0.6×	83 1.2×	57 1.0×	18 0.4×	31	881
Giuseppe Casalicchio	178 0.9×	99 0.9×	34 0.5×	25 0.4×	56 1.2×	20	623
Duco Veen	103 0.5×	90 0.8×	65 0.9×	25 0.4×	16 0.3×	28	829
Dayanand N. Naik	84 0.4×	149 1.3×	217 3.0×	48 0.8×	35 0.7×	40	873
Valentin Todorov	105 0.5×	80 0.7×	208 2.9×	25 0.4×	56 1.2×	43	780
G. Enderlein	86 0.5×	46 0.4×	134 1.9×	29 0.5×	23 0.5×	58	878
JJ Allaire	104 0.5×	144 1.3×	53 0.7×	45 0.8×	35 0.7×	26	684
Philipp Probst	177 0.9×	101 0.9×	27 0.4×	15 0.3×	50 1.0×	17	863

Countries citing papers authored by Michail Tsagris

Since Specialization

Citations

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

Fields of papers citing papers by Michail Tsagris

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Michail Tsagris

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

All Works

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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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