PhD Student at Inria Lille
My research interests evolve around differentially private and distributed
optimization for machine learning applications, including but not limited to:
- Differentially private empirical risk minimization.
- Optimization in general.
- Federated and decentralized learning.
- Imputation of missing data.
- Inference attacks on machine learning models.
- Fair machine learning.
- Robust statistics.