Numerical methods for computational and data science

The research group in numerical methods for computational and data science merges together analytical approaches and numerical techniques to address the solution of optimization problems arising in real-world applications.

Specific fields are:

Nonsmooth and nonconvex optimization

  • Optimization and big data
  • First order methods
  • High performance computing

Numerical methods for image processing and machine learning

  • Imaging and inverse problems
  • Machine learning techniques
  • Applications in medicine, engineering and astronomy

 

Staff researchers:
Silvia Bonettini, Federica Porta, Marco Prato, Simone Rebegoldi , Luca Zanni