Massimo Bertolini

125 papers receiving 2.6k citations

Massimo Bertolini's Hit Papers

Machine Learning for industrial applications: A comprehensive literature review 2021 · 388 citations
3880+1+3Years since publication100200300

Peers

Massimo Bertolini
Comparison fields: 5 of 150
  • Algebra and Number Theory 404
  • Geometry and Topology 682
  • Mathematical Physics 653
  • Medical Laboratory Technology 75
  • Industrial and Manufacturing Engineering 449
Replace Milind Sohoni with:
Milind Sohoni India
Alfredo G. Hernández‐Díaz Spain
N. Viswanadham India
Werner Römisch Germany
Aart van Harten Netherlands
Alexander Martín Germany
Muhammad Riaz Pakistan
W.H.M. Zijm Netherlands
Justo Puerto Spain
Janny Leung Hong Kong
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Citations per year

Countries citing papers authored by Massimo Bertolini

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Bertolini

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 134 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Machine Learning for industrial applications: A comprehensive literature review
Hit paper breakdown →
2021388
2 2005181
3 2004170
4 2006134
5 2009113
6 199687
7 200979
8 200573
9 201369
10 200765
11 200461
12 201159
13 201652
14 200952
15 199850
16 200648
17 199747
18 201744
19 201338
20 202037

About Massimo Bertolini

Massimo Bertolini is a scholar working on Geometry and Topology, Mathematical Physics, Industrial and Manufacturing Engineering, Algebra and Number Theory and Media Technology, having authored 134 papers that have together received 2.9k indexed citations. Recurring topics across this work include Algebraic Geometry and Number Theory (36 papers), Advanced Algebra and Geometry (32 papers), RFID technology advancements (20 papers), Advanced Manufacturing and Logistics Optimization (18 papers), Analytic Number Theory Research (15 papers), Food Supply Chain Traceability (12 papers), Scheduling and Optimization Algorithms (11 papers) and Optical Network Technologies (8 papers). The work is most often cited by research in Algebra and Number Theory (404 citations), Geometry and Topology (682 citations), Mathematical Physics (653 citations), Medical Laboratory Technology (75 citations) and Industrial and Manufacturing Engineering (449 citations). Massimo Bertolini has collaborated with scholars based in Italy, Canada and Germany. Frequent co-authors include Henri Darmon, Maurizio Bevilacqua, Francesco Zammori, Mattia Neroni, Davide Mezzogori, Marcello Braglia, Eleonora Bottani, Giovanni Romagnoli, Antonio Rizzi and Roberto Massini. Their work appears in journals such as Duke Mathematical Journal, Expert Systems with Applications, Journal of Food Engineering, American Journal of Mathematics and Production Planning & Control.

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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