Valentino Pediroda

510 citations
33 papers · 359 indexed · h-index 10

Valentino Pediroda

29 papers receiving 329 citations

Peers

Valentino Pediroda
Comparison fields: 5 of 71
  • Statistics, Probability and Uncertainty 84
  • Computational Theory and Mathematics 141
  • Computational Mechanics 99
  • Environmental Engineering 38
  • Aerospace Engineering 65
Replace Rémi Lafage with:
Rémi Lafage France
C. F. Jeff Wu United States
Kevin Tucker United States
Wenbin Song China
Jerome P. Jarrett United Kingdom
Lavi Rizki Zuhal Indonesia
Christophe Tribes Canada
Sudeepta Mondal United States
GT Parks United Kingdom
Nhu Van Nguyen South Korea
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Citations per year

Countries citing papers authored by Valentino Pediroda

Since Specialization
Citations

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

Fields of papers citing papers by Valentino Pediroda

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 19 scholars most cited alongside Valentino Pediroda, 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 Valentino Pediroda Line = papers co-authored together Valentino Pediroda links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20230
3 202310
4 20202
5 20183
6 20092
7
Quantification of thermodynamic uncertainties in real gas flows
20091
8 200914
9 20089
10 20083
11 20085
12 200812
13 200812
14 20081
15
MULTI CRITERIA CREDIT RATING (MCCR): A CREDIT RATING ASSIGNMENT PROCESS FOR ITALIAN ENTERPRISES ACCORDING TO BASEL II
20083
16 200710
17 20072
18 20053
19 20058
20 2000164

About Valentino Pediroda

Valentino Pediroda is a scholar working on Statistics, Probability and Uncertainty, Computational Theory and Mathematics and Accounting, having authored 33 papers that have together received 359 indexed citations. Recurring topics across this work include Probabilistic and Robust Engineering Design (15 papers), Advanced Multi-Objective Optimization Algorithms (11 papers), Turbomachinery Performance and Optimization (5 papers), Wind and Air Flow Studies (4 papers), Optimal Experimental Design Methods (4 papers), Heat Transfer and Optimization (3 papers), Refrigeration and Air Conditioning Technologies (3 papers) and Financial Distress and Bankruptcy Prediction (3 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (84 citations), Computational Theory and Mathematics (141 citations) and Computational Mechanics (99 citations). Valentino Pediroda has collaborated with scholars based in Italy, France and Netherlands. Frequent co-authors include Carlo Poloni, Paola Cinnella, Pietro Marco Congedo, Stefano Pieri, Diego Micheli, Paolo Giudici, Daniel Felix Ahelegbey, Shigeru Obayashi, Jacques Peter and Giovanni Mosetti.

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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