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For the Inventor, By the Inventor

Cupertino, CA, United States of America

Yinglian Xie

USPTO Granted Patents = 25 

Average Co-Inventor Count = 3.5

ph-index = 11

Forward Citations = 326(Granted Patents)


Company Filing History:

goldMedal16 out of 54,638 
 
Microsoft Technology Licensing, LLC
 patents
silverMedal9 out of 12 
 
Datavisor, Inc.
 patents

Years Active: 2011-2022

where 'Filed Patents' based on already Granted Patents

25 patents (USPTO):
1. 11539716 - Online user behavior analysis service backed by deep learning models trained on shared digital information (2022-12-27),
2. 11522873 - Detecting network attacks (2022-12-06),
3. 11232364 - Automated rule recommendation engine (2022-01-25),
4. 10771497 - Using IP address data to detect malicious activities (2020-09-08),
5. 10135788 - Using hypergraphs to determine suspicious user activities (2018-11-20),
6. 10129288 - Using IP address data to detect malicious activities (2018-11-13),
7. 10110616 - Using group analysis to determine suspicious accounts or activities (2018-10-23),
8. 10098069 - Determining cause of energy spike using energy reports (2018-10-09),
9. 10009358 - Graph based framework for detecting malicious or compromised accounts (2018-06-26),
10. 9787640 - Using hypergraphs to determine suspicious user activities (2017-10-10),
11. 9235396 - Optimizing data partitioning for data-parallel computing (2016-01-12),
12. 9148434 - Determining populated IP addresses (2015-09-29),
13. 8997220 - Automatic detection of search results poisoning attacks (2015-03-31),
14. 8856360 - Automatically identifying dynamic internet protocol addresses (2014-10-07),
15. 8789171 - Mining user behavior data for IP address space intelligence (2014-07-22),

Title: Innovations and Contributions of Yinglian Xie in Technology

Introduction

Yinglian Xie, based in Cupertino, CA, has made significant contributions to the field of technology, particularly in online user behavior analysis and network security. With a notable portfolio of 25 patents, Xie's work showcases innovative methods and systems that leverage advanced technologies such as deep learning and unsupervised machine learning for enhancing online security.

Latest Patents

Xie's latest patents include a groundbreaking service for online user behavior analysis. This service utilizes deep learning models trained on shared digital information to enhance online fraud protection. One key method involves receiving a query related to a user account on an online service, which is then processed by a deep neural network model to predict potential fraudulent activity. This model is trained on anonymized event data collected from various online service providers, providing reliable predictions to mitigate risks.

Another of Xie's innovative patents focuses on detecting network attacks. This patent details methods and systems for identifying suspicious activities across multiple accounts associated with a specific entity. By extracting relevant features from input data and employing unsupervised attack ring detection, this system identifies clusters of accounts that exhibit strong similarities or correlations, enabling proactive responses to potential network threats.

Career Highlights

Throughout his career, Yinglian Xie has worked with prominent companies, including Microsoft Technology Licensing, LLC, and Datavisor, Inc. His expertise has contributed to the development of robust technologies aimed at protecting digital environments and enhancing user trust in online services.

Collaborations

Xie's collaborations with talented professionals such as Fang Yu and Martin Abadi further highlight the innovative mindset he brings to his projects. These partnerships have fostered a creative environment that encourages the exchange of ideas and the advancement of technology in cybersecurity and data protection.

Conclusion

Yinglian Xie's contributions to technology through his patent portfolio exemplify the importance of innovation in combating online fraud and enhancing network security. His work not only demonstrates a deep understanding of complex systems but also signals a commitment to improving the safety and reliability of online interactions. Through continued research and collaboration, Xie is likely to remain a significant figure in the field, driving forward advancements that benefit both companies and users in the digital landscape.

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