Mountain View, CA, United States of America

Lei Li


Average Co-Inventor Count = 3.0

ph-index = 1

Forward Citations = 12(Granted Patents)


Company Filing History:


Years Active: 2020

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1 patent (USPTO):Explore Patents

Title: Lei Li - Innovator in Human Inspired Question Answering

Introduction

Lei Li is an accomplished inventor based in Mountain View, CA (US). He has made significant contributions to the field of artificial intelligence, particularly in the area of question answering systems. His innovative work focuses on creating methodologies that mimic human-like understanding and response to inquiries.

Latest Patents

Lei Li holds a patent for "Systems and methods for human inspired simple question answering (HISQA)." This patent describes systems and methods for automatically answering questions such as "Where did Harry Potter go to school?" The invention utilizes carefully built knowledge graphs to provide rich sources of facts. It addresses the challenge of answering factual questions in natural language, which can vary greatly in phrasing. The HISQA methodology employs deep neural networks to facilitate automatic question answering through a knowledge graph. The process begins with entity linking to identify the correct entity, followed by determining the appropriate relation to answer the question, utilizing deep gated recurrent networks and a neural embedding mechanism.

Career Highlights

Lei Li is currently employed at Baidu USA LLC, where he continues to develop innovative solutions in artificial intelligence. His work has garnered attention for its potential applications in various fields, including education and information retrieval.

Collaborations

Lei has collaborated with notable colleagues, including Zihang Dai and Wei Xu, who contribute to the advancement of AI technologies.

Conclusion

In summary, Lei Li is a pioneering inventor whose work in human inspired question answering systems represents a significant advancement in artificial intelligence. His contributions are shaping the future of how machines understand and respond to human inquiries.

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