Dr. Kevin Smith

Professor

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Biography

Kevin Smith is a Professor at the Royal Institute of Technology (Kungliga Tekniska Högskolan) in Sweden, leading research in the Computer Vision and Biomedical Image Analysis fields. His work focuses on the intersection of machine learning, medicine, and biology, particularly in building learning systems that can adapt to new data and work effectively alongside human experts. Smith's research includes developing joint Human-AI systems that enhance clinical workflows, and he also specializes in model adaptation and generalization methods. His contributions involve techniques for limited supervision and interpretability, ensuring AI-generated insights are trustworthy. As part of his collaborative efforts, he has partnered with clinicians from Karolinska Institutet and researchers from AstraZeneca, resulting in AI systems that have undergone rigorous testing in clinical trials for cancer screening. Prior to his current position, he held research roles at ETH Zurich and EPFL.

Research Interests

Computer Vision Biomedical Image Analysis Machine Learning Joint Human-AI Systems Model Adaptation Interpretability Generative Modeling Inverse Problems

Experience

Professor

2015-01-01 — Present

Royal Institute of Technology • Stockholm, Sweden

Lead the Computer Vision Biomedical Image Analysis group and collaborate with various institutions on research and clinical applications.

Courses

Applied Programming Computer Science, Part 2 (DD1324) Deep Learning Methods Biomedical Image Analysis (FDD3020) Foundations Machine Learning (DD1420) Integrating Course in Machine Learning (DD2301) Survey group select topics computer science (FDD3021)

Requirements for Royal Institute of Technology

Master Program
Requirements
GPA Requirement
Required:3.7
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
Writing
Required:61
Overall
Required:62
Prerequisites
Bachelor's degree (180 ECTS) in a relevant field Calculus in one variable Linear Algebra Probability Theory and Statistics
Application Checklist
  • Certificates and diplomas from previous university studies
  • Transcript of completed courses and grades
  • Proof of English proficiency
  • Copy of passport
  • Curriculum Vitae (CV)
  • Letter of Motivation
  • Summary sheet (if required by program)
  • Letters of Recommendation (standard for most programs)
Specialization Notes

Specific requirements apply to all departments. For Architecture, a portfolio is mandatory and submitted via a separate KTH system.