This inventor holds 2 USPTO granted patents and 3 published patent applications. Top assignee: Snap Inc.. Active years: 2025-2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2025-2026
Title: Zhenpeng Zhou: Innovator in Visual Augmentation Technology
Introduction
Zhenpeng Zhou is a notable inventor based in Newark, CA, who has made significant contributions to the field of visual augmentation technology. His innovative work focuses on enhancing video content through machine learning techniques. With a single patent to his name, Zhou is recognized for his unique approach to visual effects in video items.
Latest Patents
Zhou's patent, titled "Embeddings representing visual augmentations," involves a sophisticated method for processing input video items that include target visual augmentations. The invention utilizes a machine learning model to generate an embedding, which serves as a vector representation of the visual effect associated with the target augmentation. The model is trained in an unsupervised manner to minimize loss between training video representations across various training sets, each containing different video items with predefined visual augmentations. This innovative approach allows for the effective mapping of visual augmentations to specific identifiers based on the generated embeddings.
Career Highlights
Zhenpeng Zhou is currently employed at Snap Inc., a company known for its focus on augmented reality and multimedia applications. His work at Snap Inc. places him at the forefront of technological advancements in visual effects and user engagement through innovative video content.
Collaborations
Zhou collaborates with talented individuals such as Patrick Poirson and Maksim Gusarov, contributing to a dynamic team that drives innovation in visual technology.
Conclusion
Zhenpeng Zhou's contributions to visual augmentation technology exemplify the impact of innovative thinking in the realm of video processing. His patent and work at Snap Inc. highlight the potential for machine learning to transform how visual effects are integrated into multimedia content.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
