Xiang Lan

Title: **Innovative Contributions of Xiang Lan in Data Processing**

Introduction

Xiang Lan, an accomplished inventor based in Beijing, China, has made significant strides in the field of data processing through his innovative patents. With a total of seven patents to his name, he demonstrates a profound understanding of the intersection between technology and data management.

Latest Patents

Among his latest patents is a pioneering **data processing method and apparatus based on a recurrent neural network**. This method incorporates multiple recurrent units, which consist of various data processing nodes and a start node. A unique feature of this design is its ability to optimize the processing of target data by introducing a tagging mechanism that halts processing when certain conditions are met. Additionally, he has developed a **method for processing data** that utilizes an electronic device for efficient data handling. This innovative approach includes obtaining attribute information of input data and selecting operator implementation modes based on this information, thus enhancing the effectiveness of data operations.

Career Highlights

Xiang has worked at notable companies, including **Beijing Baidu Netcom Science Technology Co., Ltd.** and **Beijing Baidu Netcom Science and Technology Co., Ltd.**, where he contributed his expertise to cutting-edge projects in data processing and artificial intelligence. His career has been marked by a commitment to developing solutions that harness the power of data for better decision-making and computational efficiency.

Collaborations

Throughout his career, Xiang Lan has collaborated with esteemed colleagues, including Yanjun Ma and Dianhai Yu. These partnerships have fostered an environment of innovation and creativity, leading to the development of impactful technologies that continue to shape the industry.

Conclusion

Xiang Lan's contributions to data processing technology through his innovative patents exemplify the vital role inventors play in advancing our understanding of data management. His work not only highlights the capabilities of recurrent neural networks but also addresses practical challenges in processing data effectively. As he continues to innovate, the implications of his work are sure to resonate throughout the tech landscape.