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Yang Li

Welcome to my homepage! I'm a pre-tenure associate professor at Tsinghua Berkeley Shenzhen Institute (TBSI) and Tsinghua-Shenzhen Interntional Graduate School, Tsinghua University.

My overall research interest is developing efficient learning algorithms for uncertain, heterogeneous data. Most of my works exploit the intrinsic, shared structures in collections of data, to solve challenges in collective analysis of spatial trajectories, multi-modal learning and transfer learning. Applications of my research cover a wide range of problems, including

  • image-based computer vision and medical image processing

  • mobility computing and smart transportation

  • interactions of mobile agents

My current work focuses on incorporating information theory and optimization concepts into transfer learning, where we aim to answer fundamental questions such as how transferable are features between different tasks and domains, and how to learn robust models across many small domains.

I obtained my PhD. degree in Computer Science from Stanford University in 2017, advised by Leonidas Guibas. My dissertation explores how to find shared structures in large GPS trajectories under uncertainty, and how the shared structures can be used to solve challenging problems. See the Research page for details about my past projects. I was also a contributor to the KINARI project.

Curriculum Vitae

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Information Building, Rm 1108A
Tsinghua Shenzhen International Graduate School
Shenzhen, Guangdong, China (518055)