Dr. Martin Vetterli

Professor

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Biography

Martin Vetterli is an expert in the field of signal processing, particularly known for his work in wavelets, filter banks applications, and inverse problems. His research often explores theories related to sampling theory and sparsity, focusing on innovative areas such as high-quality art rendering and sensor networks. He has been involved in various projects funded by distinguished organizations, including the Swiss National Science Foundation and the European Research Council, as well as industrial partnerships with notable companies like Qualcomm and Google. Vetterli has contributed significantly to the field through multiple publications in esteemed journals, presenting findings on image representation techniques and communication theories. His teaching endeavors encompass online education in digital signal processing, indicating a commitment to broader educational outreach. Throughout his esteemed career, he has been recognized with several prestigious awards from IEEE, highlighting his impact and contributions to signal processing and communications research.

Research Interests

Experience

Professor

2000-01-01 — Present

École Polytechnique Fédérale de Lausanne • Lausanne, Switzerland

Held the position of Professor at EPFL, involved in various research and teaching activities concerning signal processing and communications.

Awards

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IEEE Jack S. Kilby Signal Processing Medal

2016-01-01
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IEEE SPS Award

2011-01-01
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EURASIP Technical Achievement Award

2008-01-01
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IEEE Signal Processing Society Technical Achievement Award

2001-01-01

Requirements for École Polytechnique Fédérale de Lausanne

Master Program
Requirements
GPA Requirement
Required:3.2
IELTS
Listening
Required:6.5
Reading
Required:6.5
Writing
Required:6.5
Speaking
Required:6.5
Overall
Required:7
TOEFL
Listening
Required:20
Reading
Required:20
Writing
Required:20
Speaking
Required:20
Total
Required:100
Prerequisites
Bachelor's degree in a related field Strong foundation in Calculus, Linear Algebra, and Probability Proficiency in programming (Python, Java, or C++)
Application Checklist
  • Curriculum Vitae
  • Copy of University Degree(s)
  • Official Transcripts
  • Statement of Purpose
  • Copy of Passport or Identity Card
  • Three Letters of Recommendation
  • Proof of English Proficiency
Specialization Notes

Standard requirements for Engineering and Basic Science Master's programs. Architecture requires an additional portfolio.