Titolo della tesi

A Study on Data Imbalance: Using Metrics on Input Data to Foresee Bias and Fairness in Classification Outcomes

Argomento di ricerca

Software engineering; Data ethics; Data quality; Algorithmic fairness; Automated decision making.

Tutori

• Marco Torchiano
• Antonio Vetro'

• Best paper award at EGOV-2020:the paper titled "Identifying Risks in Datasets for Automated Decision–Making" (presented on September 1, 2020) has been selected as the best paper in the category "The most innovative research contribution or case study" at the "EGOV2020 – IFIP EGOV-CeDEM-EPART 2020" conference. (2020)
• I participated in the IEEE WSAIM Young Professional Pitch Competition 2021, held online on December 14, 2021, by presenting the pitch entitled "Effects of Data Quality on Software Application Bias and Mitigation Strategies, Techniques and Tools". (2022)

Corso di laurea magistrale

• Sistemi informativi aziendali. A.A. 2020/21, INGEGNERIA GESTIONALE. Collaboratore del corso
• Sistemi informativi aziendali. A.A. 2021/22, INGEGNERIA GESTIONALE. Collaboratore del corso
• Sistemi informativi aziendali. A.A. 2022/23, INGEGNERIA GESTIONALE. Collaboratore del corso

Corso di laurea di 1° livello

• Visualizzazione dell'informazione quantitativa. A.A. 2020/21, INGEGNERIA INFORMATICA. Collaboratore del corso
• Visualizzazione dell'informazione quantitativa. A.A. 2021/22, INGEGNERIA INFORMATICA. Collaboratore del corso

• Mecati, Mariachiara; Torchiano, Marco; Vetro, Antonio; De Martin, Juan Carlos (2023)
  Measuring Imbalance on Intersectional Protected Attributes and on Target Variable to Forecast Unfair Classifications. In: IEEE ACCESS, vol. 11, pp. 26996-27011. ISSN 2169-3536
  Contributo su Rivista
• 
  . FAIR Data Collection
• Mecati, Mariachiara; Adrignola, Andrea; Vetro, Antonio; Torchiano, Marco (2022)
  Identifying Imbalance Thresholds in Input Data to Achieve Desired Levels of Algorithmic Fairness. In: 2022 IEEE International Conference on Big Data (IEEE BigData 2022) - Second International Workshop on Data Science for equality, inclusion and well-being challenges (DS4EIW 2022), Osaka (Japan), 17-20 December 2022, pp. 4700-4709
  Contributo in Atti di Convegno (Proceeding)
• Mecati, Mariachiara; Vetro', Antonio; Torchiano, Marco (2022)
  Detecting Risk of Biased Output with Balance Measures. In: ACM JOURNAL OF DATA AND INFORMATION QUALITY, vol. 14. ISSN 1936-1955
  Contributo su Rivista
• Mecati, Mariachiara; Vetro, Antonio; Torchiano, Marco (2021)
  Detecting Discrimination Risk in Automated Decision-Making Systems with Balance Measures on Input Data. In: 2021 IEEE International Conference on Big Data (IEEE BigData 2021) - First International Workshop on Data Science for equality, inclusion and well-being challenges (DS4EIW 2021), Orlando, FL, USA, 15-18 Dec. 2021, pp. 4287-4296. ISBN: 978-1-6654-3902-2
  Contributo in Atti di Convegno (Proceeding)
• Vetrò, Antonio; Torchiano, Marco; Mecati, Mariachiara (2021)
  Reproducibility Package for 'A Data Quality Approach to the Identification of Discrimination Risk in Automated Decision Making Systems'.
  Altro
• Vetro', Antonio; Torchiano, Marco; Mecati, Mariachiara (2021)
  A data quality approach to the identification of discrimination risk in automated decision making systems. In: GOVERNMENT INFORMATION QUARTERLY, vol. 38. ISSN 0740-624X
  Contributo su Rivista
• Labate, Demetrio; Pahari, Basanta R.; Hoteit, Sabrine; Mecati, Mariachiara (2020)
  Quantitative methods in ocular fundus imaging: Analysis of retinal microvasculature. In: ATFA19: Aspects of Time-Frequency Analysis, Torino (ITA), June 25-27, 2019, pp. 157-174. ISSN 2296-5009. ISBN: 978-3-030-56005-8
  Contributo in Atti di Convegno (Proceeding)
• Mecati, Mariachiara (2020)
  Different shades of “FAIRNESS” in automated decision-making.
  Altro
• Mecati, Mariachiara; Cannavò, Flavio Emanuele; Vetrò, Antonio; Torchiano, Marco (2020)
  Reproducibility Package for 'Identifying risks in datasets for automated decision–making'.
  Altro