Beijing, China

Wenjun Zeng

USPTO Granted Patents = 10 

Average Co-Inventor Count = 3.4

ph-index = 3

Forward Citations = 25(Granted Patents)


Location History:

  • Columbia, MO (US) (2011 - 2015)
  • Plano, TX (US) (2016)
  • Beijing, CN (2018 - 2020)
  • Redmond, WA (US) (2019 - 2021)

Company Filing History:


Years Active: 2011-2021

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10 patents (USPTO):

Title: Innovations of Wenjun Zeng

Introduction

Wenjun Zeng is a prominent inventor based in Beijing, China. He has made significant contributions to the field of technology, particularly in neural networks and coding schemes. With a total of 10 patents to his name, Zeng's work has had a substantial impact on various applications.

Latest Patents

One of his latest patents is titled "Neural network-based action detection." This invention relates to a neural network-based action detection scheme that optimizes the model based on the importance of different frames. The design allows for higher weights to be assigned to frames that are more critical for action recognition, while less important frames receive lower weights. Another notable patent is "Hybrid digital-analog coding." This innovation proposes a hybrid coding scheme that selects digital or analog encoding at the chunk level of a frame. The encoding is based on the expected distortion caused by analog transmission over a communication channel, which is estimated based on available transmission resources.

Career Highlights

Wenjun Zeng has worked with notable companies such as Microsoft Technology Licensing, LLC and Future Wei Technologies, Inc. His experience in these organizations has allowed him to develop and refine his innovative ideas.

Collaborations

Throughout his career, Zeng has collaborated with talented individuals, including Cuiling Lan and Junliang Xing. These partnerships have contributed to the advancement of his research and inventions.

Conclusion

Wenjun Zeng's contributions to technology through his patents and collaborations highlight his role as a leading inventor in the field. His work continues to influence advancements in neural networks and coding methodologies.

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