PhD Student
Erika Sottocorno
PhD student from 2025. Master’s at Milano-Bicocca (with D. Gerosa) on machine learning for stellar evolution. Her research focuses on gravitational-wave population inference with machine learning: simulation-based inference to constrain binary population models from gravitational-wave observations, combining Bayesian inference with neural density estimation. She has also published on electromagnetic searches for massive black hole binaries.
Population inferenceSimulation-based inferenceMachine learning
Paper
- Can a time-evolving, asymmetric broad line region mimic a massive black hole binary?
E. Sottocorno, M. Ogborn, L. Bertassi, F. Rigamonti, M. Bonetti, M. Eracleous, M. Dotti · arXiv:2504.06340 · Astron. Astrophys. 708, A153 (2026)