Recent & Upcoming Events

Talks, Workshops, & Lessons

Thirty-minute hands-on to introduce the useful tools available in {ggplot2} to start exploring in practice how to use text in plots.

Recent Posts

I’m very excited to announce the third release of {depigner} (Lanera 2021) to CRAN, now in the version 0.8.4. Pigna [pìn’n’a] is the …

I’m very excited to announce the second release of {depigner} to CRAN, now in the version 0.8.3. Pigna [pìn’n’a] is the Italian word …

I’m very excited to announce the first release of {depigner} to CRAN! Pigna [pìn’n’a] is the Italian word for pine cone. In jargon, it …

Accuratezza, Sensibilità, Specificità, Prevalenza, Valore Predittivo Positivo e Negativo di un test diagnostico Preambolo La biologia è …

Introduzione Ciao a tutti, oggi una collega ha avuto un problema con le età in una base di dati. In particolare, esistevano due colonne …

Shiny Apps

.js-id-Shiny-app

covid19ita

A platform for the monitoring of COVID-19 infection diffusion in Italy.

Clumpr

Current transpLant sUrplus Management Protocol in R.

Equationer

Calculator for energy requirements in elderly patients.

Grouper

Generator for students’ allocation between breakout rooms and exams’ turns.

Paper @UBEP

Scopus interface to UBEP’s published papers.

Experience

 
 
 
 
 

Research Grant: Development of a monitoring, forecasting and decision support system for the post-pandemic phase of the COVID-19 epidemic in Veneto Region

University of Padova

Jul 2020 – Present Padova (IT)
Responsibilities include:

  • Contribute to the collection of historical data on phase 1, interfacing with the various actors that hold the necessary information (Veneto Region, Azienda Zero, Health Authorities)
  • Organize the databases so that they are interoperable with each other and verify their correctness with numerical and graphic statistical techniques;
  • Construct Phase 2 impact scenarios through micro-simulation techniques. Given the dynamic aspect of updating the databases used, an interface will be developed that allows the constant updating of the database and an automatic analysis of the updated data.
 
 
 
 
 

Research Grant: Review and development of Machine Learning techniques applied in risk assessment related to food safety

University of Padova

Oct 2019 – Jun 2020 Padova (IT)
Responsibilities include:

  • review of Machine Learning (ML) techniques
  • scripting, documenting and executing ML projects and case-studies
  • setup and managment of distributed computing
  • writing scientific papers to reporting results, and presenting them national and international congresses
  • teaching insights learned.
 
 
 
 
 

Exchange J1 Visitor Student: Research Science Technologies

University of Pennsylvania

Jun 2019 – Sep 2019 Philadelphia (PA)
 
 
 
 
 

Teacher: Basic R programming for statisticians

Società di Scienze Farmacologiche Applicate

Jul 2018 – Jul 2018 Milano (IT)
Topics:

  • Basics of R and its packages system
  • Data structures
  • Data import, export and connections
  • Bases on programming in R
  • Base plot system
  • Regression Modelling Strategies and the rms package.
 
 
 
 
 

Teacher: Advance R programming for statisticians

Società di Scienze Farmacologiche Applicate

Nov 2017 – Nov 2017 Milano (IT)
Topics:

  • data manipulation
  • Grammar of Graphics with ggplot2.
 
 
 
 
 

Teacher: Basic R programming for statisticians

Società di Scienze Farmacologiche Applicate

Apr 2017 – Apr 2017 Milano (IT)
Topics:

  • Basics of R and its packages system
  • Data structures
  • Data import, export and connections
  • Bases on programming in R
  • Base plot system.
 
 
 
 
 

Consultants

Zetaresearch s.r.l.

Jan 2016 – Present Trieste (IT)
Responsibilities include:

  • Data cleaning
  • Statistical Analyses.
 
 
 
 
 

Research Grant: Review and development of Machine Learning techniques applied in risk assessment related to food safety

University of Padova

Feb 2015 – Sep 2016 Padova (IT)
Responsibilities include:

  • setup LaTeX template for the reports
  • review of Machine Learning (ML) techniques
  • scripting, documenting and executing ML projects and case-studies
  • managment of distributed computing
  • reporting and presenting the results obtained
  • teaching insights learned.
 
 
 
 
 

Fellowship: Evaluation of the risk of suffocation incident in Brazil

ProChild Protecting Children Onlus

Jan 2015 – Jan 2015 Padova (IT)
Responsibilities include:

  • LaTeX report design, development and mantaining
  • Data cleaning.

Accomplishments

Deep Learning Specialization

Courses Included:

  • Neural Network and Deep Learning (certificate)
  • Improving Deep Neural Networks: Hyperparameter tuning, Regularization and Optimization (certificate)
  • Structuring Machine Learning Projects (certificate)
  • Convolutional Neural Networks (certificate)
  • Sequence Models (in progress) (certificate)
See certificate

Mastering Software Development in R Specialization

Courses Included:

See certificate

Extending the Tidyverse (by Hadley Wickham)

Topics investigated include:

  • package development and documentation
  • test-driven development and continuous integration
  • object-oriented and functional programming
  • tidy-evaluation
  • sharing project (CRAN and GitHub)

Data Visualization with ggplot2

Parts:

  • part 1: introduction, data, aesthetics, geometries, qplot and wrap-up (certificate)
  • part 2: statistics, coordinates and facets, themes, best practices, case study (certificate),

Survival Data Analysis for Cancer Data (by Matthieu Resche-Rigon and Sylvie Chevret)

Topics investigated include (personal notes available here, R codes included):

  • Introduction to survival data
  • Regression models for survival data
  • Introduction of the competing risks framework
  • Multistate modeling for multivariate survival data
  • Modeling clustered survival data.

Conceptual Foundation of Epidemiologic Study Design (by Kenneth Rothman)

Topics investigated include:

  • Causation and Causal Inference
  • Epidemiologic Measures of Occurrence
  • Measures of Effect
  • Introduction to Basic Study Types
  • Cohort Studies
  • Case-control Studies
  • Principles of Study Design
  • Matching
  • Principles of Data Analysis

Regression Modelling Strategies (by Frank E. Harrell Jr.)

Topics investigated include:

  • validation of model assumptions
  • presenting model results
  • estimating the shape of the relationship between predictors and response
  • over-fitting and methods for data reduction
  • model validation (bootstrap and cross-validation)
  • introduction to the R rms package

Master R Developer (by Hadley Wickham)

Topics investigated include:

  • fundation of R
  • functional programming
  • object-oriented programming
  • metaprogramming
  • R packages

Data Science Specialization

Courses included

  • R Programming (certificate)
  • The Data Scientist’s Toolbox (certificate)
  • Getting and Cleaning Data (certificate)
  • Reproducible Research (certificate)
  • Exploratory Data Analyses (certificate)
  • Statistical inference (certificate)
  • Regression Models (to do)
  • Practical Machine Learning (to do)
  • Developing Data Products (to do)
  • Data Science Capstone (to do)

Recent Publications

The present study aims at providing a first look at the impact of the containment measures on the outbreak progression in the Veneto …

We combined four machine learning techniques and four data preprocessing for class imbalance to identify the outperforming strategy to …

Skills

Programming

Packages, Shiny Apps, and {learnr}
RStudio Certified Trainer in the {tidyverse}

Reproducible Research

R Markdown, $\LaTeX$,
{renv}, Docker

Machine Learning

Supervised Strong-Validation
Sequential Models

Text Mining

Electronic Health Records
Registries for Clinical Trials

Biostatistics

Regression and Survival Analysis
Epidemiologic Study Design

Graphics

{ggplot2}

Free Climbing

6a+ (on-sight) / 6c+ (redpoint)

Limitless sleeping

Record: 25.5 hours continuosly
can fall asleep anytime/where

Contact