🏆 Finalist — NIH Data Sharing Index (“S-Index”) Challenge

Paolo Manfredi

ORCID: 0000-0002-0574-8945
Decision SciencesEngineeringPhysics and AstronomyComputer Science

Pilot corpus only

This score is computed over theSindex pilot corpus and does not cover the full scientific literature. Scores are relative to papers we have ingested — papers, authors, and institutions outside the pilot are not represented. Methodology.

Top 100%percentile
0Author DataRank

Indexed papers

2in pilot corpus
datarank_citation_only_1hop_v6· scope data_onlyMethodology
Why this DataRank?

An author's DataRank is the sum of the DataRanks of all 2 indexed papers attributed to them. A prolific author with many moderate-impact papers can outrank one with a single high-impact paper.

Author scores recompute whenever paper DataRanks are refreshed, so this number lags the underlying paper scores by at most one batch run.

Read the full methodology →

Papers

Driven by 2 papers. Top paper: “A Perturbative Stochastic Galerkin Method for the Uncertainty Quantification of Linear Circuits”.

A Perturbative Stochastic Galerkin Method for the Uncertainty Quantification of Linear Circuits

IEEE Transactions on Circuits and Systems I: Regular Papers(2020)10.1109/tcsi.2020.2987470
N/A
0.786DataRank · unranked
18 citations

Riccardo Trinchero, Dries Vande Ginste, Paolo Manfredi

Efficiency of the Perturbative Stochastic Galerkin Method for Multiple Differential PCB Lines

2018 IEEE Electrical Design of Advanced Packaging and Systems Symposium (EDAPS)(2018)10.1109/edaps.2018.8680876
N/A
0.260DataRank · unranked
1 citations

Flavia Grassi, Paolo Manfredi, Dries Vande Ginste, Xinglong Wu