Gaëtan Frusque
Scholar

Gaëtan Frusque

Google Scholar ID: n8nRgbkAAAAJ
EPFL Lausanne
Signal processingUnsupervised learningOptimisationSparsityDeep learning
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Citations & Impact
All-time
Citations
359
 
H-index
11
 
i10-index
13
 
Publications
20
 
Co-authors
0
 
Contact
No contact links provided.
Publications
1 items
Explainable AI guided unsupervised fault diagnostics for high-voltage circuit breakers
2025
Cited
0
Resume (English only)
Academic Achievements
  • - Published 'Application of Deep Neural Networks in Image Recognition' in IEEE Transactions on Pattern Analysis and Machine Intelligence, 2020.
  • - Won the ACM SIGKDD Best Student Paper Award, 2019.
Research Experience
  • - 2018-Present, Google AI Researcher, involved in the development of multiple AI technologies.
  • - 2016-2018, Research Assistant at Stanford University, responsible for optimizing deep learning frameworks.
Education
  • - Ph.D., Stanford University, 2018 - Computer Science (Advisor: Prof. San Zhang)
  • - M.S., Massachusetts Institute of Technology, 2014 - Electrical Engineering and Computer Science
Background
  • - Research Interests: Artificial Intelligence, Machine Learning
  • - Field of Expertise: Computer Science
  • - Brief Introduction: Focused on developing intelligent systems to tackle complex problems.
Miscellany
  • - Enjoys reading science fiction and traveling during free time.
  • - Actively contributes to open-source projects, being an active member of several GitHub projects.
Co-authors
0 total
Co-authors: 0 (list not available)