cv | Ema's site

2017
PhD

Queen Mary, University of London, London, UK
- Explored black hole physics problems (the information paradox) using holography (AdS/CFT correspondence), a technique from string theory that allows to map a problem in gravitational physics onto a problem in particle physics in one fewer dimension.
- Analytical work using real, complex and functional analysis, differential geometry, algebra and topology.
- Work was carried out as part of an international collaboration and culminated in three published peer-reviewed papers.
2014
Msc in Physics

Università di Milano-Bicocca, Milan, Italy
- Specialized in theoretical physics.
- Attended courses in group theory, quantum field theory, statistical mechanics, general relativity, numerical methods in statistical mechanics (molecular dynamics, Monte Carlo Markov Chains).
- Finished with mark 110/110 with honours.
2011
Bsc in Physics

Università di Milano-Bicocca, Milan, Italy
- Finished with mark 110/110 with honours.

2024
Postdoctoral researcher

Bocconi University, Milan, Italy
- Researcher within the MilaNLP group working on Natural Language Processing.
2023
Postdoctoral researcher

University of Milan-Bicocca, Milan, Italy
- Member of the EXPANSION collaboration to apply data science to problems in particle physics (accelerators physiscs) and biomedical engineering (medical imaging).
2023
High school teacher

Liceo Classico Giosuè Carducci, Milan, Italy
- Teacher of maths and physics in an italian public high school.
- Taught to around 150 students with age ranging from 14 to 19.
2021 - 2023
Lead data scientist

Various companies
- Responsible for managing teams of data scientists and product analysts, including consultancy work.
- On top of the technical work I gained experience in managing people and negotiating with stakeholders both internally (product and project managers, other teams) and externally (clients).
2017 - 2021
Data scientist

Various companies (UK and Italy)
- Technical work in data science, from building reports based on data to the development and deployment of machine learning algorithms, with a specialization in optimization and operational research (logistics).
- Worked on the analytics side of things as well, defining and tracking business and technical KPIs and discussing roadmaps with product managers.

2021-now
Bayesian explorations
- A collection of explorations in the field of Machine Learning an Bayesian statistics.

2017
- Finalist for the "Best graduate teacher" award at Queen Mary, University of London, London, UK

Machine learning.
- Deep learning, including Bayesian deep learning.
- Natural language processing.
Bayesian methods.
- Probabilistic programming languages.
- Applications to machine learning.
- Estimation with Monte Carlo methods.