Dr. Hans Knutsson

Professor

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Biography

Hans Knutsson is a Professor Emeritus at Linköping University with over 400 publications in image processing and machine learning. His work has garnered more than 4000 citations, yielding an h-index of 40. He is a founding member of the Center for Medical Image Visualization (CMIV) and has supervised 21 PhD students. Receiving his PhD in 1982, he completed a Postdoctoral Fellowship at Rockefeller University in the Neurobiology Laboratory under the guidance of Nobel Laureate Torsten Wiesel from 1984 to 1986. Knutsson is notable for developing novel methods for representing and estimating local structures in multi-dimensional signals using tensors, leading to the creation of 'Normalized Convolution' for handling irregularly sampled data. His research focuses on advanced spatio-temporal filtering, data registration, and segmentation techniques. He introduced Canonical Correlation for fMRI analysis in magnetic resonance imaging (MRI) and has achieved significant results in real-time fMRI and medical image data denoising. Collaborating with Harvard Medical School's Laboratory for Mathematics Imaging, he has initiated a research line aimed at creating a theoretical framework for sampling and visualization of in vivo diffusion processes using MRI. He coordinates projects such as 'Seeing organ function', funded by the Knut and Alice Wallenberg Foundation.

Research Interests

Requirements for Linköping University

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:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:90
Prerequisites
Bachelor's degree with a major relevant to the program At least 30 ECTS credits in mathematics/applied mathematics and/or application of mathematics
Application Checklist
  • Certificates and diplomas from previous university studies
  • Transcript of records
  • Proof of English proficiency
  • Copy of passport/ID
  • Syllabus for relevant courses
Specialization Notes

Requirements are standardized across the Faculty of Science and Engineering (Institute of Technology) for international Master's programs.