November 2021 – December 2021: Course “Numerical methods and machine learning algorithms for solution of inverse problems”. Master/PhD students can contact me for registration :


The 30 Jyväskylä Summer school, 9.08.2021 – 13.08.2021

Course schedule: 9-13.8.2021, everyday 13-15 AM (lecture) + 16-18(Lab). [All Finnish time]. Swedish time: everyday 12-14 AM (lecture) + 15-17(Lab).

The course in computational sciences “COM5: Machine learning in inverse and ill-posed problems”, see more info at

COM5: Machine learning in inverse and ill-posed problems

Link in educational system CANVAS (more info with lectures, video, description of projects and possibility of submitting course projects)

Zoom link for lectures:

Meeting ID: 673 5165 6441

P.: 746622

Computer Projects:

Project 1: Regularized algorithms for detection of tumours in microwave
medical imaging

Project 2: Regularized Least squares and machine learning algorithms for
classification problem

Project 3: Principal Component Analysis for image recognition

JSS30: Lecture 1

JSS30: Comp. Lab. 1

JSS30: Lecture 2

JSS30: Comp.Lab. 2

JSS30: Lecture 3

JSS30: Comp.Lab 3

JSS30: Lecture 4

JSS30: Comp.Lab. 4

JSS30: Lecture 5

JSS30: Comp.Lab.5


May 2021: PhD position in Applied Mathematics in the field of CIPs


November 2020 – January 2021: Course “Machine learning algorithms for inverse problems”

November – December 2019: Course “Introduction to inverse and ill-posed problems”

Registration for PhD students should be done by sending mail to

and for Master’s students – sending mail to

The first lecture will be at 5 November, 13.15 -15.00 at MVL14 at the Dep. of Mathematics, Chalmers Tvärgata 3.  Dates will be: Tuesdays, Thursdays 13.15-15.00

Examination  at this course consists  in the oral presentation of one of the comp.projects which can be done in groups by 2-4 students. Description of all projects:

Lecture 1

Lecture 1 – PETSc Project

Lecture 2

Lecture 3

Lecture 3 (C++/PETSc project)

Lecture 4

Lecture 5

Lecture 6

Lecture 7

Lecture 8

Lecture 9

Lecture 10

Lecture 11