Thomas Winkle
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Researcher
Graduate Student Researcher
Research Areas
Biography and Research Information
OverviewAI-generated summary
Thomas Winkle's research focuses on the application of machine learning techniques to predictive diagnostics in power electronics. His work involves developing scalable edge-machine learning solutions designed to identify and anticipate potential failures in power electronic systems. This approach aims to enhance the reliability and maintenance strategies for these critical components.
Winkle collaborates with other researchers at the University of Arkansas at Fayetteville, including Kenneth Mordi, Wesley G. Schwartz, and Anna Corbitt, with whom he has co-authored publications. His recent work includes a 2025 publication titled "A Scalable Edge-ML Solution for Power Electronic Predictive Diagnostics."
Metrics
- Publications: 1
Selected Publications
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A Scalable Edge-ML Solution for Power Electronic Predictive Diagnostics (2025)
Collaboration Network
Top Collaborators
- A Scalable Edge-ML Solution for Power Electronic Predictive Diagnostics
- A Scalable Edge-ML Solution for Power Electronic Predictive Diagnostics
- A Scalable Edge-ML Solution for Power Electronic Predictive Diagnostics
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