Giulia CEREDA

Ruolo attuale:: Professore Associato
SSD:: STAT-01/A - Statistica
Afferenza organizzativa:: Dipartimento di Statistica, Informatica, Applicazioni 'G. Parenti' (DiSIA)

Recapiti

	0552751525
	giulia.cereda(AT)unifi.it

Avvisi

Calendario delle lezioni di Statistica industriale

Le lezioni di Statistica Industriale inizieranno il giorno 17/09 alle ore 16. Le lezioni seguenti saranno però nelle seguenti date: 01/10 ore 16-18 02/10 ore 14-17 Le lezioni di 18, 24, 25 settembre verranno recuperate in seguito

Giulia CEREDA

Orario di ricevimento (aggiornato al 12/09/2022)

Giovedi' ore 15:00-16:00

E' necessario inviare una mail per fissare un appuntamento.

Giulia CEREDA

Curriculum

Esperienze Lavorative

2025 - present: Professore Associato (PA)

Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, University of Florence

2022 - 2024: Ricercatore a tempo determinato di tipo B (RTD-b)

Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, University of Florence

2021 - 2022: Assegnista di ricerca

Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, University of Florence

2019 - 2021: Post doc Mobility fellowship,Swiss National Science Foundation (SNSF)

Leiden University and University of Florence

2016 - 2019: Specialista di Metodi Scientifici

Ufficio Federale di Statistica (Neuchatel, CH)

Formazione

2011 - 2016: Dottorato congiunto in Statistica

Mathematical Institute, Leiden University and School of Criminal Justice, University of Lausanne

2011: Laurea Magistrale in Mathematica

Dipartimento di MAtematica "G. Enriquez", Università degli Studi di Milano

2009: Laurea Triennale in Mathematica

Dipartimento di MAtematica "G. Enriquez", Università degli Studi di Milano

Interessi di Ricerca

Statistica Forense, Statistica Medica, Machine Learning

Giulia CEREDA

Pubblicazioni

Legenda

Contributo su rivista |

Articolo su libro |

Libro |

Contributo in atti di convegno (proceeding) |

Brevetto |

Curatela | Altro

Altro |

Tesi di Dottorato

Grazzini, Cosimo; Spera, Giorgia; Castellana, Daniele; Morelli, Stefania; Pilli, Elena; Baccini, Michela; Cereda, Giulia (2025). Biogeographical Ancestry Prediction via an Innovative Panel: Difficult Task or Complex Phenomenon?. In: Scientific Meeting of the Italian Statistical Society, Enrico di Bella; Vincenzo Gioia; Corrado Lagazio; Susanna Zaccarin, pp. 363-368, ISBN:9783031959943 DOI

Grazzini, Cosimo; Spera, Giorgia; Morelli, Stefania; Castellana, Daniele; Cosenza, Giulia; Baccini, Michela; Cereda, Giulia; Pilli, Elena (2025). Predictive modeling of biogeographical ancestry using a novel SNP panel and supervised learning approaches. EXPERT SYSTEMS WITH APPLICATIONS, pp. 0-0, ISSN:0957-4174 DOI

Baccini, Michela; Pirona, Federico; Grisotto, Laura; Cereda, Giulia; Lachi, Alessio; Levi, Miriam; Carreras, Giulia (2025). Tracheal, bronchus, and lung cancer mortality and air pollution exposure in Tuscany, Italy: Bayesian Health Impact Assessment and Global Sensitivity Analysis on a sub-regional scale. ENVIRONMENTAL POLLUTION, vol. 368, pp. 0-0, ISSN:0269-7491 DOI

Alessio Lachi, Cecilia Viscardi, Giulia Cereda, Giulia Carreras, Michela Baccini (2024). A compartmental model for smoking dynamics in Italy: a pipeline for inference, validation, and forecasting under hypothetical scenarios. BMC MEDICAL RESEARCH METHODOLOGY, vol. 24, pp. 0-0, ISSN:1471-2288 DOI

Giulia Cereda; Fabio Corradi; Cecilia Viscardi (2023). Learning the two parameters of the Poisson–Dirichlet distribution with a forensic application. SCANDINAVIAN JOURNAL OF STATISTICS, vol. 50, pp. 120-141, ISSN:0303-6898 DOI

Levi, Miriam; Cereda, Giulia; Cipriani, Francesco; Voller, Fabio; Baccini, Michela (2023). Case-Control Study on the Routes of Transmission of SARS-CoV-2 after the Third Pandemic Wave in Tuscany, Central Italy. INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH, vol. 20, pp. 0-0, ISSN:1660-4601 DOI

Giulia Cereda; Fabio Corradi; Cecilia Viscardi (2023). Comparing Soft Classification Methods for the Rare Type Match Problem. In: 14th Scientific Meeting of the Classification and Data Analysis Group, Pearson, pp. 378-381, ISBN:9788891935632

Marra, Michele; Baccini, Michela; Cereda, Giulia; Culasso, Martina; De Sario, Manuela; Eboli, Ilenia; Lachi, Alessio; Mitrova, Zuzana; Saulle, Rosella; Bena, Antonella (2023). [School-based screening strategies to prevent the spread of COVID-19 in school: a systematic review of the literature]. EPIDEMIOLOGIA E PREVENZIONE, vol. 47, pp. 152-171, ISSN:1120-9763 DOI

Cereda, Giulia ; Viscardi, Cecilia ; Baccini, Michela (2022). Combining and comparing regional SARS-CoV-2 epidemic dynamics in Italy: Bayesian meta-analysis of compartmental models and global sensitivity analysis. FRONTIERS IN PUBLIC HEALTH, vol. 10, pp. 0-0, ISSN:2296-2565 DOI Accesso ONLINE all'editore

Giulia Cereda, Fabio Corradi, Cecilia Viscardi (2022). Exploiting partial knowledge to evaluate the average causal effect via an ABC perspective. In: SIS2022 - 51st Scientific Meeting of the Italian Statistical Society, Pearson, pp. 914-919, ISBN:9788891932310

Baccini M.; Cereda G. (2021). Screening plans for SARS-CoV-2 based on sampling and rotation: An example in a European school setting. PLOS ONE, vol. 16, pp. 0-0, ISSN:1932-6203 DOI

Baccini M.; Cereda G.; Viscardi C. (2021). The first wave of the SARS-CoV-2 epidemic in Tuscany (Italy): A SI2R2D compartmental model with uncertainty evaluation. PLOS ONE, vol. 16, pp. 0-0, ISSN:1932-6203 DOI

Michela Baccini, Giulia Cereda (2021). The second wave of SARS-CoV-2 epidemic in Italy through a SIRD model. In: SIS 2021, Pearson, pp. 1718-1723, ISBN:9788891927361

Giulia Cereda; Fabio Corradi (2020). A change of glasses strategy to solve the rare type match problem. In: 50th Meeting of the Italian Statistical Society, Pisa, June 2020, Pearson, pp. 614-619, ISBN:9788891910776

Giulia Cereda; Cecilia Viscardi; Anna Gottard; Fabrizia Mealli; Michela Baccini (2020). Analisi e previsioni dell’epidemia da SARS-CoV-2 in Toscana / Analysis and future scenarios of the SARS-CoV-2 epidemic in Tuscany Region (Central Italy). EPIDEMIOLOGIA E PREVENZIONE, vol. 44, pp. 120-127, ISSN:1120-9763 DOI

Cereda, G. ; Gill, R. D. (2020). A nonparametric Bayesian approach to the rare type match problem. ENTROPY, vol. 22, pp. 0-0, ISSN:1099-4300 DOI

Cereda G.; Gill R.D.; Taroni F. (2018). A solution for the rare type match problem when using the DIP-STR marker system. FORENSIC SCIENCE INTERNATIONAL: GENETICS, vol. 34, pp. 88-96, ISSN:1872-4973 DOI

Cereda,G. (2017). Current challenges in statistical DNA evidence evaluation. (Tutor: Richard D. Gill, Franco Taroni)

Cereda G. (2017). Impact of Model Choice on LR Assessment in Case of Rare Haplotype Match (Frequentist Approach). SCANDINAVIAN JOURNAL OF STATISTICS, vol. 44, pp. 230-248, ISSN:0303-6898 DOI

Cereda G. (2017). Bayesian approach to LR assessment in case of rare type match. STATISTICA NEERLANDICA, vol. 71, pp. 141-164, ISSN:0039-0402 DOI

Cereda, G; Biedermann, A ; Hall, D; Taroni, F (2014). Object-oriented Bayesian networks for evaluating DIP-STR profiling results from unbalanced DNA mixtures. FORENSIC SCIENCE INTERNATIONAL: GENETICS, vol. 8, pp. 159-169, ISSN:1872-4973 DOI

Cereda G.; Biedermann A.; Hall D.; Taroni F. (2014). An investigation of the potential of DIP-STR markers for DNA mixture analyses. FORENSIC SCIENCE INTERNATIONAL: GENETICS, vol. 11, pp. 229-240, ISSN:1872-4973 DOI

Giulia CEREDA

Curriculum

Work Experience

2025 - present: Assciate Professor (PA)

Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, University of Florence

2022 - 2024: Assistant Professor (RTD-b)

Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, University of Florence

2021 - 2022: Post-doctoral Fellow (Assegnista di ricerca)

Dipartimento di Statistica, Informatica, Applicazioni “G. Parenti”, University of Florence

2019 - 2021: Post doc Mobility fellowship,Swiss National Science Foundation (SNSF) grant

Leiden University and University of Florence

2016 - 2019: Specialist of Statistical Methods

Swiss Federal Statistical Office (Neuchatel, CH)

Education

2011 - 2016: Joint Phd in Applied Statistics

Mathematical Institute, Leiden University and School of Criminal Justice, University of Lausanne

2011: MsC Mathematics

Dipartimento di MAtematica "G. Enriquez", Università degli Studi di Milano

2009: BsC Mathematics

Dipartimento di MAtematica "G. Enriquez", Università degli Studi di Milano

Research interests

Forensic Statistics, Medical Statistics, Machine Learning