Karina Gibert

Associate Professor

Universitat Politècnica de Catalunya

Spain

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About

Karina Gibert is an Associate Professor at Universitat Politècnica de Catalunya, Spain. Her research areas include topic modelling, clustering techniques, and the impact of the digital revolution on urban systems. She has published recent articles addressing the ethical implications of technology, data analysis methods for diverse datasets, and the socio-economic effects of the COVID-19 pandemic.

Articles (7)

Year:

2023

Year:

2023

Year:

2022

Year:

2022

Year:

2022

Year:

2021

Year:

2021

Collaborators (2)

Massimiliano Giacalone

ITALY

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Manel Poch

Professor

Universitat de Girona

SPAIN

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Karina Gibert

Research Interests

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Articles (7)

Variable Selection for Meaningful Clustering of Multitopic Territorial Data

A Unified Formal Framework for Factorial and Probabilistic Topic Modelling

The Digital Revolution in the Urban Water Cycle and Its Ethical–Political Implications: A Critical Perspective

Women in Artificial Intelligence

Bootstrap–CURE: A Novel Clustering Approach for Sensor Data—An Application to 3D Printing Industry

Distribution-Based Entropy Weighting Clustering of Skewed and Heavy Tailed Time Series

The INSESS-COVID19 Project. Evaluating the Impact of the COVID19 in Social Vulnerability While Preserving Privacy of Participants from Minority Subpopulations

Collaborators (2)

Massimiliano Giacalone

Manel Poch

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Karina Gibert

Research Interests

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About

Articles (7)

Variable Selection for Meaningful Clustering of Multitopic Territorial Data

A Unified Formal Framework for Factorial and Probabilistic Topic Modelling

The Digital Revolution in the Urban Water Cycle and Its Ethical–Political Implications: A Critical Perspective

Women in Artificial Intelligence

Bootstrap&ndash;CURE: A Novel Clustering Approach for Sensor Data&mdash;An Application to 3D Printing Industry

Distribution-Based Entropy Weighting Clustering of Skewed and Heavy Tailed Time Series

The INSESS-COVID19 Project. Evaluating the Impact of the COVID19 in Social Vulnerability While Preserving Privacy of Participants from Minority Subpopulations

Collaborators (2)

Massimiliano Giacalone

Manel Poch

Make your next move.

Bootstrap–CURE: A Novel Clustering Approach for Sensor Data—An Application to 3D Printing Industry