Massimo Dipierro

428 citations
11 papers · 239 · h-index 5

Impact in

    • Particle physics theoretical and experimental studies
    • Quantum Chromodynamics and Particle Interactions
    • High-Energy Particle Collisions Research
    • Neutrino Physics Research
    • Spam and Phishing Detection

Papers in

Massimo Dipierro

10 papers receiving 228 citations

Peers

Massimo Dipierro
Comparison fields: 5 of 43
  • Nuclear and High Energy Physics 95
  • Information Systems 110
  • Signal Processing 51
  • Sociology and Political Science 110
  • Artificial Intelligence 41
Replace Paolo Bolzoni with:
Paolo Bolzoni Germany
J. Volmer Netherlands
P. Elmer United States
L. Lechner Austria
Jyotsna Singh India
Praveen Manoharan Germany
B. Koblitz Switzerland
Hyun Duk Kim United States
Zakhar Shumaylov United Kingdom
Jeremiah Onaolapo United Kingdom
Massimo Dipierro relative to Paolo Bolzoni Germany Paolo Bolzoni's profile →
Citations per field
00.5×10×
Paolo Bolzoni · 1×
Citations per year

Countries citing papers authored by Massimo Dipierro

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Dipierro

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

11 of 11 papers shown
#Work
1 2018120
2 200596
3 20186
4 20215
5
Web2py Enterprise Web Framework, 2nd Ed
20084
6 20203
7 20142
8 20141
9 20181
10 20081
11 20080

About Massimo Dipierro

Massimo Dipierro is a scholar working on Nuclear and High Energy Physics, Computer Networks and Communications, Information Systems and Management, Artificial Intelligence and Sociology and Political Science, having authored 11 papers that have together received 239 indexed citations. Recurring topics across this work include Particle physics theoretical and experimental studies (3 papers), Quantum Chromodynamics and Particle Interactions (2 papers), Computational Physics and Python Applications (2 papers), Distributed and Parallel Computing Systems (2 papers), Advanced Data Storage Technologies (2 papers), Scientific Computing and Data Management (2 papers), High-Energy Particle Collisions Research (2 papers) and Complex Network Analysis Techniques (1 paper). The work is most often cited by research in Nuclear and High Energy Physics (95 citations), Information Systems (110 citations), Signal Processing (51 citations), Sociology and Political Science (110 citations) and Artificial Intelligence (41 citations). Massimo Dipierro has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Marco L. Della Vedova, Stefano Moret, Luca de Alfaro, C. Bérnard, A. X. El-Khadra, Andreas S. Kronfeld, D. Menscher, M. B. Oktay, Paul B. Mackenzie and R. Sugar. Their work appears in journals such as Computing in Science & Engineering, Physical Review Letters, The Journal of Risk Finance, SHILAP Revista de lepidopterología and Proceedings of 31st International Symposium on Lattice Field Theory LATTICE 2013 — PoS(LATTICE 2013).

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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