people

The Inria MALICE team, whose members have a strong expertise in statistical learning, applied mathematics, statistics and optimization, develops algorithmic and theoretical research focused on integrating physical knowledge into machine learning models.

• Eduardo Brandao, Associate Professor (Inria, UJM, France).
  physics, laser-matter interaction
• Amaury Habrard, Professor (Inria, UJM, France).
  statistical learning theory, physics-informed machine learning
• Jordan Patracone, Associate Professor (Inria, UJM, France), Head of DYNAMO.
  numerical optimization, physics-informed machine learning
• Marc Sebban, Professor (Inria, UJM, France), Head of MALICE.
  statistical learning theory, physics-informed machine learning

Non-Permanent Staff: Ben Gao (PhD Student), Abdel-Rahim Mezidi (PhD Student)

The Computational Statistics and Machine Learning (CSML) group conducts research at the intersection of machine learning theory and algorithm design, grounded in mathematics and statistics, with particular emphasis on empirical processes and numerical optimization.

• Vladimir Kostic, Researcher (IIT, Italy), Associate Professor (Univ. Novi Sad, Serbia).
  numerical computing, statistical learning theory, Markov transfer operators
• Massimiliano Pontil, Senior Researcher (IIT, Italy), Professor (UCL, UK), Head of CSML.
  statistical learning theory, neural operators, dynamical systems
• Saverio Salzo, Associate Professor (La Sapienza, Italy), Visiting Scientist (IIT, Italy).
  numerical optimization

Non-Permanent Staff: Riccardo Grazzi (Postdoc), Erfan Mirzaei (PhD Student), Pietro Novelli (Postdoc).