Dr. Mattias Sandberg

Instructor

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Biography

Mattias Sandberg is a university lecturer at KTH Royal Institute of Technology, specializing in analytical and numerical methods for differential equations, as well as stochastic differential equations and machine learning. He teaches various advanced courses, where he also serves as course coordinator and examiner. His expertise lies in the application of computational methods within engineering mathematics, focusing on sustainable development and research methodology in mathematics. Mattias is involved in guiding students through their theses in computation engineering at an advanced level. His research interests and pedagogical approach emphasize the importance of numerical analysis and the implementation of machine learning techniques in solving complex mathematical problems.

Research Interests

Analytical Methods Numerical Methods Differential Equations Stochastic Differential Equations Machine Learning

Courses

Analytical and Numerical Methods for Differential Equations Analytical and Numerical Methods for Partial Differential Equations and Transforms Computational Methods for Stochastic Differential Equations Thesis Work in Computational Engineering, Advanced Level Sustainable Development and Research Methodology in Mathematics

Requirements for KTH Royal Institute of Technology

Master Program
Requirements
GPA Requirement
Required:3
IELTS
Listening
Required:5.5
Reading
Required:5.5
Writing
Required:5.5
Speaking
Required:5.5
Overall
Required:6.5
TOEFL
Listening
Required:0
Reading
Required:0
Writing
Required:20
Speaking
Required:0
Total
Required:90
PTE
Listening
Required:0
Reading
Required:0
Writing
Required:62
Speaking
Required:0
Overall
Required:62
Prerequisites
Bachelor's degree (180 ECTS) in Science, Engineering, or a related field. Specific course requirements vary by department (e.g., Mathematics, Programming, or Subject-specific credits).
Application Checklist
  • Certificates and diplomas of completed degree
  • Transcript of records
  • Proof of English proficiency
  • Copy of passport or ID
  • Curriculum Vitae (CV)
  • Letter of Motivation
  • Letters of Recommendation (if required by program)
  • Summary of Project (if required)
Specialization Notes

Master's programs are organized under Schools; departments listed are units within these schools (e.g., EECS, ABE, CBH, ITM, SCI).