Davide Pigoli

Davide Pigoli

King's College

H-index: 10

North America-United States

About Davide Pigoli

Davide Pigoli, With an exceptional h-index of 10 and a recent h-index of 8 (since 2020), a distinguished researcher at King's College, specializes in the field of Functional data analysis, Spatial statistics, Statistical methods for non Euclidean data, Object Data Analysis.

His recent articles reflect a diverse array of research interests and contributions to the field:

Statistics in Phonetics

Predicting class switch recombination in B-cells from antibody repertoire data

Characterisation and modelling of lightning strikes as point events in time and space

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers

Estimation of temperature-dependent growth profiles for the assessment of time of hatching in forensic entomology

Statistical design and analysis for robust machine learning: a case study from COVID-19

Mathematical foundations of functional Kriging in Hilbert spaces and Riemannian manifolds

A large-scale and PCR-referenced vocal audio dataset for COVID-19 (preprint)

Davide Pigoli Information

University

Position

Department of Mathematics

Citations(all)

550

Citations(since 2020)

339

Cited By

363

hIndex(all)

10

hIndex(since 2020)

8

i10Index(all)

11

i10Index(since 2020)

8

Email

University Profile Page

Google Scholar

Davide Pigoli Skills & Research Interests

Functional data analysis

Spatial statistics

Statistical methods for non Euclidean data

Object Data Analysis

Top articles of Davide Pigoli

Statistics in Phonetics

arXiv preprint arXiv:2404.07567

2024/4/11

Davide Pigoli
Davide Pigoli

H-Index: 8

Morgan Sonderegger
Morgan Sonderegger

H-Index: 15

Predicting class switch recombination in B-cells from antibody repertoire data

Biometrical Journal

2024/3/7

Davide Pigoli
Davide Pigoli

H-Index: 8

Franca Fraternali
Franca Fraternali

H-Index: 24

Characterisation and modelling of lightning strikes as point events in time and space

EGU General Assembly Conference Abstracts

2022/5

Davide Pigoli
Davide Pigoli

H-Index: 8

Audio-based AI classifiers show no evidence of improved COVID-19 screening over simple symptoms checkers

Nature Machine Intelligence

2024/2/7

Estimation of temperature-dependent growth profiles for the assessment of time of hatching in forensic entomology

Journal of the Royal Statistical Society Series C: Applied Statistics

2023/5

Davide Pigoli
Davide Pigoli

H-Index: 8

Statistical design and analysis for robust machine learning: a case study from COVID-19

arXiv preprint arXiv:2212.08571

2022/12/15

Mathematical foundations of functional Kriging in Hilbert spaces and Riemannian manifolds

Geostatistical Functional Data Analysis

2022/1/18

Alessandra Menafoglio
Alessandra Menafoglio

H-Index: 13

Davide Pigoli
Davide Pigoli

H-Index: 8

Kriging Riemannian data via random domain decompositions

Journal of Computational and Graphical Statistics

2021/9/16

Alessandra Menafoglio
Alessandra Menafoglio

H-Index: 13

Davide Pigoli
Davide Pigoli

H-Index: 8

Micro‐CT imaging of Onchocerca infection of Simulium damnosum s.l. blackflies and comparison of the peritrophic membrane thickness of forest and savannah flies

Medical and veterinary entomology

2021/9

Spatio-temporal clustering methodologies for point-event natural hazards

EGU General Assembly Conference Abstracts

2021/4

Davide Pigoli
Davide Pigoli

H-Index: 8

Estimation of Insect Age for Assessing Minimum Post-Mortem Interval in Forensic Entomology Casework

2020/11/5

Davide Pigoli
Davide Pigoli

H-Index: 8

Functional principal component analysis as a versatile technique to understand and predict the electric consumption patterns

Sustainable Energy, Grids and Networks

2020/3/1

Samuele Grillo
Samuele Grillo

H-Index: 14

Davide Pigoli
Davide Pigoli

H-Index: 8

O2S2 for the Geodata Deluge

2020

Alessandra Menafoglio
Alessandra Menafoglio

H-Index: 13

Davide Pigoli
Davide Pigoli

H-Index: 8

See List of Professors in Davide Pigoli University(King's College)