Lines of Research

Data Science and Machine Learning

  • 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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Operations Research

  • Mathematical optimization for complex decisions
  • Planning, routing, and resource allocation
  • Decision-making under uncertainty
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Statistical Modelling

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

  • Computational methods for biological data
  • Structural biology and biomedical imaging
  • AI for biomolecular analysis and discovery
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