Giosuè Migliorini

I am a Ph.D. Student in Statistics at UC Irvine, advised by Prof. Padhraic Smyth.

I had the privilege to spend the summer of 2023 working at Los Alamos National Laboratory, under the mentorship of Dr. Natalie E. Klein, where I applied Bayesian deep learning to scientific problems.

Before moving to the U.S., I lived and studied in Italy, where I completed my Master's in Data Science at Bocconi University. You can check out my Master's thesis on computational methods for Bayesian variable selection at this link, completed under the supervision of Prof. Giacomo Zanella at Bocconi's Bayes Lab.

Email  /  GitHub  /  Google Scholar  /  LinkedIn

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Research

I'm interested in deep generative models, optimal transport, and Bayesian deep learning.

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Dynamic Conditional Optimal Transport through Simulation-Free Flows


Gavin Kerrigan, Giosuè Migliorini, Padhraic Smyth
arXiv, 2024

We introduce a dynamic formulation of conditional optimal transport, and incorporate it into the flow matching framework. We showcase the method on challenging Bayesian inverse problems.
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Functional Flow Matching


Gavin Kerrigan, Giosuè Migliorini, Padhraic Smyth
27th International Conference on Artificial Intelligence and Statistics (Oral, Outstanding Student Paper Highlights), 2023

Theory and methodology for flow matching in infinite-dimensional spaces, for training and sampling at arbitrary resolutions.

Teaching

  • Statistical Methods II (STATS 211P - Teaching Assistant): weekly discussion sessions, office hours, and homework grading for students of the Masters of Data Science at UCI. Topics include generalized linear models, PCA, regularization, model selection, splines, mixed-effects models.
  • Introduction to Probability and Statistics (STATS 120B - Reader): undergraduate-level class focusing on maximum likelihood and hypothesis testing.
  • Introduction to Probability and Statistics for Computer Science (STATS 67 - Reader): undergraduate-level class on basic statistics and probability theory.

Education

  • Ph.D. in Statistics - University of California, Irvine (2022 - present)
  • M.Sc. in Data Science (summa cum laude) - Bocconi University (2020 - 2022)
  • B.Sc. in Economics (summa cum laude) - University of Padova (2017 - 2020)

Design and source code from Jon Barron's website