Mo Chen

Title: Mo Chen: Innovator in Federated Learning and Privacy-Preserving Computation

Introduction

Mo Chen is a prominent inventor based in Shanghai, China. He has made significant contributions to the fields of federated learning and privacy-preserving computation. With a total of four patents to his name, Chen's work is at the forefront of technological innovation.

Latest Patents

One of Mo Chen's latest patents is a "Heterogeneous processing system for federated learning and privacy-preserving computation." This invention includes a serial subsystem designed for distributing processing tasks and configuration information. The processing task indicates performing an operation corresponding to computing mode on one or more operands. Additionally, it features a parallel subsystem that selectively obtains operands from an intermediate result section while performing operations based on configuration information. Another notable patent is the "Correction apparatus and correction method." This patent describes a correction apparatus that includes a first adjustment module, multiple second adjustment modules, and a correction calculation module. The design aims to address issues related to non-ideal channels that output signals in response to drive signals with error values.

Career Highlights

Mo Chen has worked with leading technology companies, including Huawei Technologies Co., Limited and Clustar Technology Co., Ltd. His experience in these organizations has allowed him to develop and refine his innovative ideas, contributing to advancements in technology.

Collaborations

Throughout his career, Mo Chen has collaborated with notable professionals in his field, including Wei Wang and Zhiwei Zhang. These collaborations have further enhanced his work and led to impactful innovations.

Conclusion

Mo Chen's contributions to federated learning and privacy-preserving computation highlight his role as a leading inventor in the technology sector. His patents reflect a commitment to advancing the field and addressing contemporary challenges in computation.