This inventor holds 2 USPTO granted patents. Top assignee: Amazon Technologies, Inc.. Active years: 2021-2023.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
Company Filing History:
Years Active: 2021-2023
Title: Senmao Liu: Innovator in On-Demand Resource Scheduling
Introduction
Senmao Liu is a notable inventor based in Seattle, WA (US). He has made significant contributions to the field of resource scheduling, particularly through his work at Amazon Technologies, Inc. Liu holds 2 patents that showcase his innovative approach to optimizing resource allocation.
Latest Patents
Liu's latest patents focus on on-demand resource scheduling. These patents describe a system and method for scheduling resources to perform discrete tasks. The scheduling features include generating schedules that are predicted to appeal to the tasked resource, such as delivery partners, based on various factors like time, day of the week, location, and item types. By utilizing machine learning, the schedules and their terms can be dynamically generated to suit the preferences of each tasked resource while also considering the overall demand for services. The modeling incorporates historical data to account for the likelihood of an offer being accepted and the risk of cancellation for a given resource. The machine learning algorithms may be based on a mixed integer problem, constrained by partner and system capacity parameters.
Career Highlights
Senmao Liu has established himself as a key figure in the realm of resource scheduling at Amazon Technologies, Inc. His innovative work has contributed to enhancing the efficiency of resource allocation in various applications.
Collaborations
Liu has collaborated with notable coworkers, including Jose Ramon Algara Allegre and Rowan William Hale. Their combined expertise has further advanced the projects they have worked on together.
Conclusion
Senmao Liu's contributions to on-demand resource scheduling reflect his innovative spirit and dedication to improving efficiency in resource management. His work continues to influence the field and showcases the potential of machine learning in optimizing scheduling processes.
Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile
