Renato Berlinghieri

Renato Berlinghieri

PhD student


Welcome to my personal page! I am a 3rd year PhD student at MIT, in the department of Electrical Engineering and Computer Science, working in LIDS under the supervision of Tamara Broderick. My main research interests are machine learning (in particular generative modeling) and Bayesian inference. I am also very interested (and eager to learn more!) in optimal transport, and the way in which this is used in generative modeling, statistics, and probability.

Last summer, I interned as a Machine Learning researcher at Apple, working with Nick Foti in the Health AI team. The main goal of the internship was to develop generative models for solving discrete combinatorial optimization problems relevant to Apple Health AI team.

Before joining MIT, I completed a MSc in Data Science at Bocconi University advised by Igor Prünster, with a thesis focused on random measure approaches to Bayesian nonparametrics. Prior to that, I obtained a BSc in Economics and Computer Science advised by Massimo Marinacci, where I worked on neuroeconomics and statistical models for decision making.

Besides research, I have always been very passionate about having an active role in the communities I am part of. I am the (co-)President of the MIT EECS Graduate Students’ Association, a board member of MITaly, and a mentor at Lead The Future.

Feel free to contact me via email at renb at mit dot edu.

  • Bayesian Inference
  • Machine Learning
  • Statistical optimal transport
  • PhD in Electrical Engineering & Computer Science, 2026 (expected)

    Massachusetts Institute of Technology

  • MSc in Data Science & Business Analytics, 2021

    Bocconi University

  • BSc in Economics & Computer Science, 2019

    Bocconi University

Recent news

  • June 2023: I have been selected as a Student Poster Award winner at the 36th New Englang Statistics Symposium.

  • May 2023: I am excited to share I will be in Seattle for the summer interning at Apple, doing research in the Health AI team!

  • February 2023: I won the Best Presentation Award for the talk on ‘‘Gaussian Processes at the Helm(holtz)’’ at 28th Annual LIDS Student Conference, Optimization and Algorithms Session :)

  • July 2022: I have been selected as a Poster Award winner in the category BayesComp/j-ISBA at ISBA 2022.

  • June 2022: I won the Microsoft Award for the best talk at BAYSM 2022!


Recent publications