Pennington, NJ, United States of America

Xin Zhang


Average Co-Inventor Count = 9.0

ph-index = 1

Forward Citations = 5(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Innovator Xin Zhang: Pioneering Telecommunications with Deep Learning

Introduction

Xin Zhang is an accomplished inventor based in Pennington, NJ (US). He has made significant contributions to the field of telecommunications through his innovative work in predicting received signal strength using advanced deep learning techniques. His expertise and dedication to research have led to the development of a patented technology that enhances the efficiency of telecommunication networks.

Latest Patents

Xin Zhang holds a patent for a groundbreaking method titled "Predicting received signal strength in a telecommunication network using deep neural networks." This computer-implemented method involves receiving geographic data and antenna information, inputting this data into a convolutional neural network, and predicting the received signal strength at various locations. The technology aims to improve the reliability of wireless communications by accurately forecasting signal strength based on geographic and technical parameters.

Career Highlights

Xin Zhang is currently employed at Future Wei Technologies, Inc., where he continues to push the boundaries of innovation in telecommunications. His work has not only contributed to the advancement of technology but has also positioned him as a key player in the industry. With a focus on deep learning applications, he is at the forefront of developing solutions that address the challenges faced by modern telecommunication networks.

Collaborations

Xin collaborates with talented professionals in his field, including Jin Yang and Jie Ren. These partnerships foster a creative environment that encourages the exchange of ideas and the development of cutting-edge technologies.

Conclusion

Xin Zhang's contributions to telecommunications through his innovative patent demonstrate his commitment to advancing the field. His work exemplifies the potential of deep learning in enhancing communication networks, paving the way for future innovations.

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