Gianvito Pio

Assistant Professor

University of Bari Aldo Moro

Italy

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Gianvito Pio is an Assistant Professor at the University of Bari Aldo Moro in Italy. His research areas encompass social network analysis, machine learning applications in agriculture and finance, and legal informatics. He has authored several recent articles, including studies on user classification in social networks, anomaly prediction in cryptocurrency trends, and risk identification methodologies. His work also extends to exploring the applications of blockchain technology in the healthcare sector.

Articles (14)

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2025

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2025

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2024

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2024

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2023

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2023

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2023

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2023

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2023

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2022

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2022

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2022

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2021

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2021

Collaborators (7)

Nathalie Japkowicz

American University

UNITED STATES

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Gennaro Vessio

Assistant Professor

University of Bari Aldo Moro

ITALY

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Roberto Corizzo

Assistant Professor

American University

UNITED STATES

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Michelangelo Ceci

Full Professor

University of Bari Aldo Moro

ITALY

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Paolo Mignone

Assistant Professor

University of Bari Aldo Moro

ITALY

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Claudio Angione

Professor

Teesside University

UNITED KINGDOM

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Michiel Hochstenbach

Associate Professor

Eindhoven University of Technology

NETHERLANDS

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Gianvito Pio

Research Interests

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Articles (14)

IMMENSE: Inductive Multi-perspective User Classification in Social Networks

CARROT: Simultaneous prediction of anomalies from groups of correlated cryptocurrency trends

A novel random forest-based approach for the non-destructive and explainable estimation of ammonia and chlorophyll in fresh-cut rocket leaves

Distributed Heterogeneous Transfer Learning

Forecasting and what-if analysis of new positive COVID-19 cases during the first three waves in Italy

Multi-view overlapping clustering for the identification of the subject matter of legal judgments

HURI: Hybrid user risk identification in social networks

SAIRUS: Spatially-aware identification of risky users in social networks

On the exploitation of the blockchain technology in the healthcare sector: A systematic review

PRILJ: an efficient two-step method based on embedding and clustering for the identification of regularities in legal case judgments

Relational tree ensembles and feature rankings

Integrating genome-scale metabolic modelling and transfer learning for human gene regulatory network reconstruction

BROCCOLI: overlapping and outlier-robust biclustering through proximal stochastic gradient descent

Big Data analytics for knowledge transfer among organisms while reconstructing Gene Regulatory Networks

Collaborators (7)

Nathalie Japkowicz

Gennaro Vessio

Roberto Corizzo

Michelangelo Ceci

Paolo Mignone

Claudio Angione

Michiel Hochstenbach

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