Curriculum Vitae

Education

• PhD in Computational Mathematics, TU Vienna, Austria,  Ongoing (end approx. 3/2024)
  Project: Numerical simulation of stochastic dynamic micromagnetics
  Developed the sparse grid high dimensional interpolation library SGMethods (Python)
• MS in Computational Science and Engineering, EPFL, Switzerland, 9/2016-2/2019, GPA 5.37/6 
  Project: Trimmed isogeometric approximation of the Stokes problem
• BS in Mathematics
  University of Trento, Italy, 9/2013-7/2016, 30 cum laude

Previous Work Experience

• Intern,
  Fluxim AG, Switzerland, 2/2019-7/2019
  Research of global optimization algorithms for semiconductor simulation software. 
• Implementation in a stand-alone library and integration in company software
• Intern,
  EPFL, 3/2020-8/2020
  Research & implementation of numerical fluid mechanics algorithm (Isogeometric Analysis)

Skills

• Uncertainty quantification: Sparse Grids, Monte Carlo methods
• Finite elements, isogeometric analysis
• Local and global numerical optimization

IT Skills

• Scientific Python, Matlab
• C, C++
• Basic parallel computing in MPI, CUDA
• Git
• Paraview visualization

Transferable Skills

• Public speaking: Speaker at 10+ scientific conferences and workshops, tutor of university students for 8+ courses
• Proposal writing: Won grant for research stay at UNSW, Sydney in 2023. Total value 3500€

Publications

• Feischl M., Scaglioni A. – Convergence of adaptive stochastic collocation with finite elements, CAMWA, 2021 https://www.sciencedirect.com/science/article/pii/S0898122121002571 
• Feisch M., Scaglioni A. – Sparse Grid approximation of the stochastic Landau-Lifshitz-Gilbert problem, Preprint, 2024
  https://arxiv.org/abs/2310.11225 

Languages

• English (work proficiency)
• German (conversational/basic work proficiency)
• Italian (mother tongue),
• French (conversational)

Other commitments

• Board member and treasurer, EPFL SIAM student chapter, 2018-2019
• Student board member, Vienna School of Mathematics (excellence school), 2020-