“My goal is to increase the autonomy and applicability of machine learning systems.”
Yuhong Guo develops machine learning methodologies and algorithms to address real world challenges. The information required to perform machine learning, historically, has come from human annotated data. Guo’s research seeks to ease the compilation of annotated data in real-life applications and expand the autonomy of machine learning methods, by reducing dependence on extensive human guidance and expanding applicability to diverse annotation scenarios in domains such as medical data analysis and autonomous driving.
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