Yuke Zhu

Yuke Zhu is a researcher on the NVIDIA AI Algorithms team. He received his master’s and Ph.D. degrees from Stanford. His Ph.D. thesis centers around closing the perception-action loop to make robot intelligence more generalized and applicable to less-controlled environments. His research lies at the intersection of robotics, machine learning, and computer vision. He develops computational methods of perception and control that give rise to intelligent robot behaviors. Through his work, he aspires to teach robots to understand and interact with the visual world around them. His expertise has gained attention from a variety of news outlets, leading tech institutions, and award organizations. His publications have won several awards and nominations, including the Best Conference Paper Award in ICRA 2019. His work has been covered by media, such as MIT Technology Review and Stanford News.
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Posts by Yuke Zhu


NVIDIA Research: Fast Uncertainty Quantification for Deep Object Pose Estimation

Researchers from NVIDIA, University of Texas at Austin and Caltech developed a simple, efficient, and plug-and-play uncertainty quantification method for the... 3 MIN READ
Data Science

Building a Benchmark for Human-Level Concept Learning and Reasoning

Humans have an inherent ability to learn novel concepts from only a few samples and generalize these concepts to different situations. Even though today’s... 10 MIN READ