New York, NY, United States of America

Yinxiang Gao


Average Co-Inventor Count = 4.0

ph-index = 1


Company Filing History:


Years Active: 2025

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1 patent (USPTO):Explore Patents

Title: Innovations by Yinxiang Gao in Digital Therapeutics

Introduction

Yinxiang Gao is an accomplished inventor based in New York, NY (US). He has made significant contributions to the field of digital therapeutics, particularly through his innovative patent that addresses the simulation of testing environments for application triggers generated using machine learning. His work is pivotal in enhancing the effectiveness of digital therapeutic applications.

Latest Patents

Yinxiang Gao holds a patent titled "Automatically varying system clocks to simulate test environments for application triggers generated using machine learning." This patent outlines systems and methods for simulating testing environments for digital therapeutic applications that address various conditions over time. The computing system described in the patent selects a trigger from an event scheduler, sets a clock to the corresponding timestamp, and facilitates communication between the service and the user device. This innovative approach ensures that messages are transmitted accurately in accordance with the trigger, validating the event scheduler's functionality.

Career Highlights

Yinxiang Gao is currently employed at Click Therapeutics, Inc., where he continues to develop and refine digital therapeutic solutions. His expertise in machine learning and system simulation has positioned him as a key player in the advancement of digital health technologies.

Collaborations

Yinxiang has collaborated with notable colleagues, including Apoorv Bajaj and Ritesh Manchanda. These partnerships have fostered a collaborative environment that encourages innovation and the development of cutting-edge therapeutic applications.

Conclusion

Yinxiang Gao's contributions to the field of digital therapeutics through his innovative patent and collaborative efforts highlight his commitment to improving health outcomes through technology. His work exemplifies the intersection of machine learning and healthcare, paving the way for future advancements in the industry.

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