This inventor holds 1 USPTO granted patent and 5 published patent applications. Active years: 2026.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Years Active: 2026
Title: Mingkui Liu and Content-Adaptive Video Ladder Optimization
Introduction
Mingkui Liu is an inventor associated with Culver City, California. His patent work addresses video streaming, focusing on how content delivery systems can select and prepare video versions to better serve viewers under varying network conditions.
Latest Patents
The provided information lists one patent for Liu: “Content adaptive video ladder optimization.” The patent describes methods, systems, and computer programs for optimizing video streaming. A content delivery system obtains one or more video files and determines a set of video ladders for each file. Each ladder represents a transcoded version with particular parameters, selected to substantially maximize a measure of viewer utility. The optimization takes into account the complexity of the video content and historical network characteristics. The system then transcodes the file into the corresponding versions and stores them for delivery to user devices.
Career Highlights
Liu’s listed patent reflects an approach to video delivery that adapts transcoding choices to both the content and the network conditions viewers are likely to encounter. The supplied information identifies 1 patent associated with him.
Collaborations
Zhuqi Li and He Liu are identified as Liu’s coworkers in the provided information. Their specific contributions to the patent are not detailed.
Conclusion
Mingkui Liu’s patent on content-adaptive video ladder optimization describes a system for selecting and preparing video versions according to content complexity and historical network characteristics, with the goal of improving streaming utility for viewers.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile