Massimiliano Pavan

691 total citations
13 papers, 432 citations indexed

About

Massimiliano Pavan is a scholar working on Molecular Biology, Anthropology and Artificial Intelligence. According to data from OpenAlex, Massimiliano Pavan has authored 13 papers receiving a total of 432 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Molecular Biology, 3 papers in Anthropology and 3 papers in Artificial Intelligence. Recurrent topics in Massimiliano Pavan's work include Gene Regulatory Network Analysis (3 papers), Classical Antiquity Studies (3 papers) and Bioinformatics and Genomic Networks (3 papers). Massimiliano Pavan is often cited by papers focused on Gene Regulatory Network Analysis (3 papers), Classical Antiquity Studies (3 papers) and Bioinformatics and Genomic Networks (3 papers). Massimiliano Pavan collaborates with scholars based in Italy. Massimiliano Pavan's co-authors include Marcello Pelillo and Deno J. Geanakoplos and has published in prestigious journals such as IEEE Transactions on Pattern Analysis and Machine Intelligence, The American Historical Review and Electronic Notes in Discrete Mathematics.

In The Last Decade

Massimiliano Pavan

9 papers receiving 416 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Massimiliano Pavan Italy 5 243 176 76 69 40 13 432
Jihun Ham United States 6 319 1.3× 189 1.1× 68 0.9× 35 0.5× 64 1.6× 6 538
G. Krishna India 9 190 0.8× 289 1.6× 69 0.9× 31 0.4× 23 0.6× 23 517
Yuchi Huang United States 10 542 2.2× 211 1.2× 54 0.7× 37 0.5× 82 2.0× 16 702
Xiaowen Li China 8 249 1.0× 143 0.8× 47 0.6× 69 1.0× 28 0.7× 28 389
Sandro Vega-Pons Italy 8 190 0.8× 354 2.0× 88 1.2× 107 1.6× 51 1.3× 10 531
Erhan Gökçay Türkiye 7 111 0.5× 158 0.9× 54 0.7× 24 0.3× 21 0.5× 15 292
Jean-François Paiement United States 8 209 0.9× 120 0.7× 103 1.4× 19 0.3× 23 0.6× 13 449
Rajib Kumar Jha India 14 408 1.7× 155 0.9× 25 0.3× 55 0.8× 71 1.8× 46 570
Paulo Rauber Netherlands 8 274 1.1× 245 1.4× 60 0.8× 29 0.4× 13 0.3× 12 437
Shyh-Rong Lay United States 4 108 0.4× 277 1.6× 63 0.8× 23 0.3× 23 0.6× 8 420

Countries citing papers authored by Massimiliano Pavan

Since Specialization
Citations

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

Fields of papers citing papers by Massimiliano Pavan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Massimiliano Pavan

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

All Works

13 of 13 papers shown
1.
Pavan, Massimiliano, et al.. (2022). Survey On Feature Extraction Approach for Human Action Recognition in Still Images and Videos. International Journal of Scientific Research in Computer Science Engineering and Information Technology. 359–369. 1 indexed citations
2.
Pavan, Massimiliano & Marcello Pelillo. (2008). Dominant Sets and Hierarchical Clustering. 6 indexed citations
3.
Pavan, Massimiliano & Marcello Pelillo. (2006). Dominant Sets and Pairwise Clustering. IEEE Transactions on Pattern Analysis and Machine Intelligence. 29(1). 167–172. 270 indexed citations
4.
Pavan, Massimiliano, et al.. (2004). Scritti su Canova e il neoclassicismo.
5.
Pavan, Massimiliano & Marcello Pelillo. (2004). Efficient Out-of-Sample Extension of Dominant-Set Clusters. Neural Information Processing Systems. 17. 1057–1064. 24 indexed citations
6.
Pavan, Massimiliano & Marcello Pelillo. (2004). Unsupervised texture segmentation by dominant sets and game dynamics. 302–307. 4 indexed citations
7.
Pavan, Massimiliano & Marcello Pelillo. (2003). Image Segmentation by Dominant Sets. Electronic Notes in Discrete Mathematics. 12. 166–177. 1 indexed citations
8.
Pavan, Massimiliano & Marcello Pelillo. (2003). A new graph-theoretic approach to clustering and segmentation. I–145. 120 indexed citations
9.
Pavan, Massimiliano. (1987). Aquileia città di frontiera. OpenstarTs (Univeristy of Trieste https://www.units.it/). 2 indexed citations
10.
Pavan, Massimiliano, et al.. (1986). L'Ereditá classica nelle lingue orientali. Medical Entomology and Zoology.
11.
Pavan, Massimiliano. (1981). Vico e la filologia classica del Cinque-Seicento. 15(11). 163–172. 1 indexed citations
12.
Pavan, Massimiliano. (1977). Antichità classica e pensiero moderno. 1 indexed citations
13.
Geanakoplos, Deno J. & Massimiliano Pavan. (1965). La Politica Gotica Di Teodosio Nella Pubblicistica Del Suo Tempo. The American Historical Review. 71(1). 131–131. 2 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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