Julio Enrique Castrillon Candas

Research Interests

  • Uncertainty Quantification
  • Partial Differential Equations / Integral Equations
  • Fast Multi-Level Kriging for large spatial datasets
  • Fast Radial Basis Function Interpolation.
  • Machine Learning / Big Data


  • J.E. Castrillon-Candas, D. Liu and M. Kon. Stochastic functional analysis with applications to robust machine learning. Submitted to NeurIPS. (2021).
  • J.E. Castrillon-Candas, F. Nobile and R.F.  Tempone. A hybrid collocation-perturbation approach for PDEs with random domains. Adv Comput Math 47, 40 (2021).
  • J. E. Castrillon-Candas and J. Xu. A stochastic collocation approach for parabolic PDEs with random11domain deformations.Computers & Mathematics with Applications, 93:32–49, 2021.