間眅埶AV

"I am very impressed by his all-around abilities, ranging from fundamental research to industrial applications."

Dr. Greg Mori

Dr. Zhiwei Deng receives Deans Convocation Medal

As one of 間眅埶AV's most outstanding graduate students from the , Dr. Zhiwei Deng is being recognized with the Dean of Graduate Studies Convocation Medal. On behalf of 間眅埶AV, we congratulate Dr. Deng on his outstanding achievements.

June 08, 2020
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For his doctoral research, Dr. Zhiwei Deng pushed the frontiers of computer vision and deep learning, especially advancing graph-based models, analyzing human activities and generating human motions or gestures.  

In his research, Deng discovered and proposed a model that analyzes multi-person human activities using graph-based algorithms, which has critical applications in surveillance videos at hospitals and nursing homes. During his studies, Deng also collaborated with researchers from industrial labs, such, as Disney Research and Facebook Reality Labs, developing algorithms for analyzing human facial expression and generating human motions and gestures.

Dr. Zhiwei Deng published several top-tier conference papers, one of which was published at the top computer vision and machine learning conference. Additionally, he co-founded a robotics startup company that commercialized machine learning and computer vision algorithms developed during his PhD.

Deng's supervisor, Dr. Greg Mori, acknowledges his achievements. "I am very impressed by his all-around abilities, ranging from fundamental research to industrial applications. Zhiwei's work during his PhD was outstanding, and for these reasons, I believe his thesis work is deserving of the highest award at 間眅埶AV."

Deng is grateful for the experiences he earned while studying at 間眅埶AV. Says Deng, I spent several wonderful years working with my advisor, my labmates and other researchers at 間眅埶AV and would like to thank them for their help and insightful discussions on the research.

Dr. Zhiwei Deng is a postdoctoral researcher at Princeton University exploring empowering embodied agents in a visual environment with reasoning abilities, and continue building fundamental algorithms for graphical distribution modelling.

Additional Links

  • Academic Unit: 
  • Thesis: 
  • LinkedIn: 
  • Personal Website: /~zhiweid/

Written by Candice Chic