Curriculum Vitae

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Experience

Research Scientist

USI - Università della Svizzera italiana
  • Example 1
  • 11/2021 - 12/2024
  • Example 1
  • Lugano, Switzerland
  • Contributed to 2 European high-performance computing (HPC) projects, collaborated in different teams to achieve project goals. Lead writing of 2 grant proposals and reports for reporting to the European regulator.
  • Independently developed the first time-parallel method for cardiac simulations with 9th-order accuracy, ensuring precision and stability across 1000+ processors (Python, PDE, nonlinear Multi Grid).
  • Devised and implemented a new integration method for cardiac problems, reducing runtime by 50% with respect to the state of the art (Python, FEM, PDE).
  • Derived a boundary element formulation for cellular models in electrophysiology (C++, BEM, PDE).
  • Designed a new stochastic optimization method, improving stability of the gradient descent method for deep learning architectures (Python, ML).
  • Lectured the MSc course “Introduction to Ordinary Differential Equations,” receiving a 9/10 student rating for clear and engaging presentations.
  • Supervision of 3 MSc theses in deep learning and optimization.

Research Scientist

EPFL - Swiss Federal Technology Institute of Lausanne
  • Example 1
  • 06/2020 - 08/2021
  • Example 1
  • Lausanne, Switzerland
  • Devised and analyzed Monte Carlo numerical integrators for jump-diffusion stochastic differential equations (C++, SDE, Monte Carlo).
  • Developed mixed-precision numerical integrators for GPUs, improving computational efficiency by approximately 75%.
  • Lecturer for the MSc course “Numerical Integration of Dynamical Systems”.

PhD Student

EPFL - Swiss Federal Technology Institute of Lausanne
  • Example 1
  • 09/2015 - 05/2020
  • Example 1
  • Lausanne, Switzerland
  • Formulated multi scale methods for stochastic differential equations, achieving speed-up factors of 5 (C++, SDE, Monte Carlo).
  • Designed finite element methods for PDEs, reducing simulation time by a factor of 10 through detailed analysis and optimization (C++, PDE, FEM).
  • Supervised a thesis on simulating chemical kinetics using stabilized tau-leap methods, achieving a 50% efficiency gain (C++, SDE, Monte Carlo).
  • Supervisor for 5 BSc and MSc students in research projects.
  • Teaching assistant for mathematics courses at EPFL.

Computational scientist intern

CSCS - Swiss National Supercomputing Centre
  • Example 1
  • 09/2013 - 01/2014
  • Example 1
  • Lugano, Switzerland
  • Migrated an astrophysics simulation code from CPUs to GPUs (Fortran).
  • Optimized code, algorithms, and data structures, achieving a 10x speed-up.
  • Results presented at international conferences.

Education

PhD in Applied Mathematics

EPFL - Swiss Federal Technology Institute of Lausanne
  • Example 1
  • 09/2015 - 05/2020
  • Example 1
  • Lausanne, Switzerland

MSc in Mathematical Engineering

EPFL - Swiss Federal Technology Institute of Lausanne
  • Example 1
  • 09/2012 - 06/2014
  • Example 1
  • Lausanne, Switzerland

BSc in Mathematics

EPFL - Swiss Federal Technology Institute of Lausanne
  • Example 1
  • 09/2009 - 06/2012
  • Example 1
  • Lausanne, Switzerland

SKILLS

Applied Mathematics

  • Numerical methods for time: parallel-in-time, explicit stabilized methods, stabilization, stiff and geometric methods, nonlinear multigrid for time, mixed-precision methods, multi-scale methods, Ruge-Kutta methods, exponential methods, spectral deferred correction.
  • Numerical methods for space: finite elements, finite differences, discontinuous Galerkin, boundary elements.
  • Stochastics: stochastic calculus, probability theory, Monte Carlo methods, multi-scale integration, jump-diffusion processes, tau-leap methods, stochastic simulation algorithm.
  • Miscellaneous: dynamial systems, optimization methods, numerical linear algebra, statistics, Bayesian inference, differential equations.

Computer Science

  • Programming languages: C++, Python, MATLAB, Fortran, SQL.
  • Software development: Git, CMake, Docker, Conda.
  • Scientific computing and libraries: NumPy, JAX, pandas, Eigen.
  • Operating Systems: Linux, MacOS, Windows.
  • Documentation and writing: LaTeX, Doxygen.

Quantitative Finance

  • Pricing: Stochastic calculus, derivatives pricing, binomial asset pricing, options, risk neutral measure.

Awards

Prize in Numerical Analysis: Received international Butcher Prize for excellent communication skills and research quality.

Certification

IBM Data Science Professional Certificate

Languages

  • English: fluent
  • French: fluent
  • Italian: native
  • Portuguese: native
  • Spanish: fluent

Interests

Fermentation: Soy sauce, miso, beer, cheese, kefir, tempeh, kvass, ….