Scholar
Luca Masserano
Google Scholar ID: hJpzTpoAAAAJ
Research Scientist, Meta
Citations & Impact
Citations
86
H-index
4
i10-index
2
Publications
11
Co-authors
19
list available
Publications
Resume (English only)
Academic Achievements
- Publications and Preprints: 'On Focusing Statistical Power for Searches and Measurements in Particle Physics' (Under Review), 'Trustworthy Scientific Inference with Machine Learning' (Dissertation), 'Enhancing Foundation Models for Time Series Forecasting via Wavelet-based Tokenization' (ICML 2025). Additionally, his research was supported by the National Science Foundation (grant #2020295) and the CMU 2024 Presidential Fellowship for the Statistics Department.
Research Experience
- During his PhD, Luca focused on robust uncertainty quantification in likelihood-free settings and worked on various internships involving foundation models, probabilistic forecasting, and optimization.
Education
- PhD: Carnegie Mellon University, Joint PhD Program in Statistics and Machine Learning, advised by Ann B. Lee and co-mentored by Barnabás Póczos; M.Sc.: Bocconi University, Data Science (Statistics), advised by Igor Pruenster and Antonio Lijoi.
Background
- Luca is a recent PhD graduate from the Joint PhD Program in Statistics and Machine Learning at Carnegie Mellon University. His research interests include robust uncertainty quantification in likelihood-free settings, leveraging modern machine learning (e.g., deep generative models) to quantify the uncertainty on parameters that govern complex physical processes. He is also interested in foundation models, probabilistic forecasting, and optimization.
Miscellany
- Luca will join Meta as a Research Scientist in September 2025.
