Aimé Fournier

Member of the Center for Computational Mathematics.

Other research Interests and Applications:

general relativity, inverse problems, machine learning, seismo-electromagnetism, uncertainty quantification, wildfire simulation.

Recent Publications:

• Kochanski AK, A Fournier, Mandel J, 2018: “Experimental design of a prescribed burn instrumentation” Atmosphere 9, 296.
• P Bharadwaj, L Demanet & A Fournier “Focused blind deconvolution”, IEEE Transactions on Signal Processing 67, 2019.
• Fournier, Clerget, Bharadwaj, Merciu, Skår “A seismoelectric inverse problem with well-log data and borehole-confined acquisition”, SEG 89th Annual Meeting, 2019.
• H Wang, M Fehler & A Fournier “Assessing leak paths in the cement sheath of a cased borehole by analysis of monopole wavefield modes”, to appear in Communications in Computational Physics, 2019.

Courses taught:

• 2015 Fall: Linear Algebra and Differential Equations (14 students)
• 2016
  • Spring: Linear Algebra and Differential Equations (21 students)
  • Summer: Numerical Analysis I (17 students)
  • Fall: Topics in Applied Mathematics (7 graduate students)<
• 2017
  • Spring: Calculus II (24 students)
  • Fall: Linear Algebra and Differential Equations (14 students); Readings in Mathematics: Riemannian Geometry (5 graduate students)
• 2018
  • Spring: Numerical Analysis I (20 students); Readings in Mathematics: Gravitation and Cosmology (4 graduate students)
  • Fall: Numerical Analysis I (20 students); Readings in Mathematics: Einstein's Field Equations (4 graduate students)
• 2019
  • Spring: Calculus II (online, 22 students); Math Clinic (11 students); Readings in Mathematics: Burgers & Navier-Stokes (5 graduate students)
  • Fall: Math Clinic (9 students); Independent Study: Tensor analysis and curvature (1 graduate student)

I am also the PhD Research Advisor for Vince Herr, and serve on the PhD Comittee for Mengjie Yao.

In 2018 I advised MS projects in Mathematical and Statistical Sciences for Alexa Desautels and Maryam Khazaei Pool.