Dr. Martin Trapp

Assistant Professor

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Biography

Martin Trapp is an Assistant Professor at KTH Royal Institute of Technology specializing in probabilistic machine learning. His research interests include Bayesian deep learning, tractable models, and uncertainty quantification, as well as language models such as LLMs and VLMs. He has a background in developing rigorous statistical methods that enhance the understanding of machine learning models. As an active researcher, Trapp also focuses on contributing to the advancing field through publications and collaboration with other experts in the domain.

Research Interests

Probabilistic Machine Learning Bayesian Deep Learning Tractable Models Uncertainty Quantification Large Language Models Vision Language Models

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).