Launch week offerEnds in00h00m00s

annual Promonthly Pro

Michele Gallo

Full professor in Statistics

University of Naples - L'Orientale

Italy

Research Interests

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Explore related searches

Professors in Italy Professors in Statistics Statistics professors in Italy

About

Michele Gallo is a Full Professor in Statistics at the University of Naples - L'Orientale, Italy. His research interests encompass sports data science, reduced-rank regression, three-way principal balance analysis, and consumer engagement in the circular economy. He has contributed to various scholarly articles focusing on innovative statistical methods and their applications in management and sports analytics.

Articles (17)

Year:

2026

Year:

2025

Year:

2025

Year:

2025

Year:

2024

Year:

2024

Year:

2023

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Year:

2020

Year:

2020

Year:

2020

Year:

2020

Collaborators (1)

Maria Gabriella GRASSIA

Full professor

Università degli Studi di Napoli Federico II

ITALY

View details

ApplyKite TwinLearns as you apply

Make your next move.

Prepare your application

Review drafts before you send them.

Michele Gallo

Research Interests

Make your next move.

Explore related searches

About

Articles (17)

Modeling relative competence in PISA: a compositional multiple factor analysis approach

Editorial: special issue on sports data science

Overview of reduced-rank regression with dense and sparse coefficients, and a new estimation procedure

Robust tools for three-way component analysis of compositional data

Re-examining consumer engagement in the circular economy

Management styles and innovation

Constraint principal components for linear discrimination

A novel estimation procedure for robust CANDECOMP/PARAFAC model fitting

PCA and other dimensionality-reduction techniques

On four-way CP model estimation efficiency

Three-way principal balance analysis: algorithm and interpretation

A Compositional Three-Way Approach for Student Satisfaction Analysis

Three is a Magic Number: Evidence on the Effects of the Application of the Three-Point Rule in Italy’s Serie A

Robust distance measure to detect outliers for categorical data

Robust distance measure to detect outliers for categorical data

Detection of Outlying Cells in Contingency Tables Using Model Based Diagnostics

Detection of Outlying Cells in Contingency Tables Using Model Based Diagnostics

Collaborators (1)

Maria Gabriella GRASSIA

Make your next move.