CV

Algarve, Portugal - August 2021

Current position

• 08/2023 - ongoing, University of Padua (Italy)
  Researcher (RTDa) in Social Statistics (secs-s/05). Main project: AGE - IT - A novel public-private alliance to generate socioeconomic, biomedical and technological solutions for an inclusive Italian Ageing Society.

Previous positions

• 01/2023 - 07/2023, University of Padua (Italy)
  Postdoctoral fellow at the Department of Statistical Sciences. PRIN project founding Social and health Frailty as determinants of Inequality in Aging - SOFIA (supervisor: Prof. G. Boccuzzo).
• 04/2019 - 11/2019, European Institute of Oncology, Milan (Italy)
  Statistician at the Department of Experimental Oncology. Main interests: medical statistics, survival analysis, meta-analysis, data mining and machine learning applications in medicine (supervisor: Prof. S. Gandini).

Education

• 10/2019 - 04/2023, University of Padua (Italy)
  PhD in Statistics. Thesis: New approaches on statistical modeling for drug safety data (supervisor: Prof. G. Boccuzzo, co-supervisor: Prof. N. Tatonetti).

• 10/2016 - 03/2019, University of Padua (Italy)
  Master’s Degree in Statistical Sciences.

• 10/2013 - 09/2016, University of Padua (Italy)
  Bachelor’s Degree in Statistics.

Visiting periods

• 02/2022 - 08/2022, Columbia University (New York, USA)
  Visiting period at the Department of Biomedical Informatics.

• 08/2017 - 01/2018, Århus University (Denmark)
  Erasmus student in Mathematics and Statistics Master’s Degree.

Other work experience

• 08/2018 - 03/2019, Veneto Cancer Registry, Padua (Italy)
  Research internship for Master’s Thesis (supervisor: Dr. M. Zorzi).

• 11/2018 - 01/2019, Regional Healthcare System, Padua (Italy)
  Statistician at the Diabetology Department. Research project Statistical Evaluations of the Diabetes Screening.

Skills

• Professional
  Theoretical and applied statistics (focused on clinical data analysis), Data Mining & Machine Learning, Epidemiology, Text Mining & Sentiment Analysis, Survival Analysis.

• Programming languages and softwares
  R: data wrangling, statistical modeling, data mining & machine learning, package development, data visualization (advanced skills)
  Python, SAS: statistical modeling (basic skills)
  MS Office Suite (advanced user)
  Latex, Markdown: document creation and editing (proficient skills)
  Machine learning libraries: Keras, TensorFlow, Torch (basic skills)
  Version control: GitHub (usual user)

• Languages
  Italian: mother tongue
  English: fluent (C1)