Dr. Lars Hammarstrand

Professor

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Biography

Lars Hammarstrand is a Professor in the field of Signal Processing at Chalmers University. His research primarily focuses on the intersection of machine learning and Bayesian inference, particularly their applications in visual localization, mapping, sensor fusion, nonlinear filtering, and object tracking. He is recognized for his contributions to the field of Biomedical Engineering and Electrical Engineering. With extensive experience in his research group, he has been involved in multiple projects that explore innovative solutions in signal processing, leading to advancements in technology.

Research Interests

Machine Learning Bayesian Inference Visual Localization Mapping Sensor Fusion Nonlinear Filtering Object Tracking

Requirements for Chalmers University 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
Writing
Required:20
Total
Required:90
PTE
Listening
Required:62
Reading
Required:62
Writing
Required:62
Speaking
Required:62
Overall
Required:62
Prerequisites
Bachelor's degree in a relevant field of Engineering, Science, or Architecture Minimum 180 ECTS credits Specific course prerequisites in Mathematics (Linear Algebra, Multivariable Analysis, Statistics) Specific course prerequisites in Physics or Chemistry depending on program
Application Checklist
  • Certificates and diplomas from previous university studies
  • Transcripts of completed courses and grades
  • Proof of English proficiency
  • Proof that you meet the specific entry requirements
  • Copy of passport or ID
  • Curriculum Vitae (CV)
  • Letter of Motivation (1 page)
  • Project portfolio (required for Architecture and Design programs)
Specialization Notes

General requirements apply to all departments listed at Chalmers. Specific departments like Architecture require a portfolio. Programs in Management/Economics do not strictly require GMAT/GRE but high academic standing is prioritized.