V. Parisi

1.6k citations
62 papers · 1.1k indexed · h-index 17

V. Parisi

59 papers receiving 1.0k citations

Peers

V. Parisi
Comparison fields: 5 of 135
  • Numerical Analysis 93
  • Hepatology 110
  • Oncology 240
  • Computational Theory and Mathematics 125
  • Radiology, Nuclear Medicine and Imaging 143
Replace Liming Wu with:
Liming Wu China
Vittorio Rizzoli Italy
Weijiang Zhang China
Wenrui Hao United States
James Nichols United States
Claus Bendtsen United Kingdom
Andrzej Świerniak Poland
Rehan Ali United States
Shih-Ho Wang Taiwan
Marcel Schilling Germany
V. Parisi relative to Liming Wu China Liming Wu's profile →
Citations per field
00.5×3.6×
Liming Wu · 1×
Citations per year

Countries citing papers authored by V. Parisi

Since Specialization
Citations

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

Fields of papers citing papers by V. Parisi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20252
2 20250
3 202331
4
Montecarlo uniform sampling of high-dimensional convex polytopes: reducing the condition number with applications in metabolic network analysis
20133
5 200726
6
Multidisciplinary approach to locally advanced rectal cancer: results of a single institution trial.
20065
7 200216
8 20017
9 20013
10 20017
11 200013
12 19991
13 199857
14 19987
15 19976
16 19935
17 199316
18 199215
19 19910
20 198912

About V. Parisi

V. Parisi is a scholar working on Numerical Analysis, Archeology, Hepatology, Electrochemistry and Computational Theory and Mathematics, having authored 62 papers that have together received 1.1k indexed citations. Recurring topics across this work include Thin-Film Transistor Technologies (7 papers), Gastric Cancer Management and Outcomes (6 papers), Colorectal Cancer Surgical Treatments (5 papers), Silicon Nanostructures and Photoluminescence (5 papers), RNA and protein synthesis mechanisms (4 papers), Colorectal Cancer Treatments and Studies (4 papers), Diamond and Carbon-based Materials Research (4 papers) and Advanced Optimization Algorithms Research (4 papers). The work is most often cited by research in Numerical Analysis (93 citations), Hepatology (110 citations), Oncology (240 citations), Computational Theory and Mathematics (125 citations) and Radiology, Nuclear Medicine and Imaging (143 citations). V. Parisi has collaborated with scholars based in Italy, United States and Denmark. Frequent co-authors include Filippo Aluffi-Pentini, Francesco Zirilli, F. Cremona, Paolo Delrio, Francesco Izzo, Raffaéle Palaia, Steven A. Curley, Giuseppe Lucio Cascini, Fabiana Tatangelo and Antonio Avallone. Their work appears in journals such as ACM Transactions on Mathematical Software, Applied Surface Science, Journal of Chemotherapy, Journal of Theoretical Biology and Journal of Optimization Theory and Applications.

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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2026