Lines of Research

Data Science and Artifical Intelligence

  • Extracting new value from massive datasets
  • Speeding up ML workflows
  • Explaining and interpreting AI-driven decisions
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Applied Mathematics

  • Orthogonal polynomials and approximation theory
  • Control theory and dynamical systems
  • Geometrical integrators
  • Distributed algorithms
  • Optimization algorithms and mathematical programming
  • Learning of dynamical systems and temporal series
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Computer Science and Robotics

  • Data-driven tuning of industrial and engineering processes
  • Reducing energy and environmental footprints
  • Accelerating the training of deep learning systems
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Statistical Modelling

  • Semi-parametric regression
  • Generalized Additive Models
  • Bayesian Statistics
  • Survival Analysis
  • Mixture Models
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