Peiwen Zhong

Title: Peiwen Zhong and AI-Driven Recovery Event Prediction.

Introduction

Peiwen Zhong is an inventor based in Toronto, Canada, and is associated with The Toronto-Dominion Bank. His patent work concerns the use of artificial intelligence to predict targeted, agency-specific recovery events.

Latest Patents

The provided information lists one patent for Zhong: Predicting Targeted, Agency-Specific Recovery Events Using Trained Artificial Intelligence Processes. The disclosed systems and methods use interaction data related to an initial event to create an input dataset. A trained machine-learning or artificial-intelligence process analyzes that dataset and generates output indicating the likelihood of targeted events associated with candidate assignments during a future period. A computing system can use this output to assign the initial event to a suitable candidate assignment. Zhong’s listed portfolio includes 1 patent.

Career Highlights

Zhong’s listed invention applies trained AI processes to event prediction and assignment. The patent describes a workflow that turns interaction data into predictions intended to support decisions about how an event should be assigned. The provided information associates him with The Toronto-Dominion Bank.

Collaborations

The supplied information names Jonathan Anders James Smith and David Christopher O’Grady as Zhong’s coworkers. It does not specify their roles in the patent or describe their contributions to the invention.

Conclusion

Peiwen Zhong’s listed patent focuses on using trained AI processes to predict targeted recovery events and inform assignment decisions, reflecting an application of machine learning to operational workflows.