Growing community of inventors

San Francisco, CA, United States of America

Mark Yinan Li

Average Co-Inventor Count = 5.67

ph-index = 5

The patent ph-index is calculated by counting the number of publications for which an author has been cited by other authors at least that same number of times.

Forward Citations = 141

Mark Yinan LiAndrew Stephen Tomkins (17 patents)Mark Yinan LiShanmugasundaram Ravikumar (17 patents)Mark Yinan LiShalini Agarwal (17 patents)Mark Yinan LiBo Pang (17 patents)Mark Yinan LiMyLinh Yang (9 patents)Mark Yinan LiSteve Chien (3 patents)Mark Yinan LiJames Aspinall (3 patents)Mark Yinan LiRuwen Hess (3 patents)Mark Yinan LiMarc Andreas Schaub (3 patents)Mark Yinan LiZhou Bailiang (2 patents)Mark Yinan LiBenjamin James Anderson (2 patents)Mark Yinan LiBenjamin Ernest Anderson (1 patent)Mark Yinan LiZhou Bailiang (1 patent)Mark Yinan LiMylinh Yang (0 patent)Mark Yinan LiMark Yinan Li (20 patents)Andrew Stephen TomkinsAndrew Stephen Tomkins (124 patents)Shanmugasundaram RavikumarShanmugasundaram Ravikumar (83 patents)Shalini AgarwalShalini Agarwal (33 patents)Bo PangBo Pang (30 patents)MyLinh YangMyLinh Yang (15 patents)Steve ChienSteve Chien (7 patents)James AspinallJames Aspinall (7 patents)Ruwen HessRuwen Hess (4 patents)Marc Andreas SchaubMarc Andreas Schaub (3 patents)Zhou BailiangZhou Bailiang (31 patents)Benjamin James AndersonBenjamin James Anderson (4 patents)Benjamin Ernest AndersonBenjamin Ernest Anderson (7 patents)Zhou BailiangZhou Bailiang (2 patents)Mylinh YangMylinh Yang (0 patent)
..
Inventor’s number of patents
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Strength of working relationships

Company Filing History:

1. Google Inc. (20 from 32,543 patents)


20 patents:

1. 12203765 - Identifying, processing and displaying data point clusters

2. 11876760 - Determining strength of association between user contacts

3. 11835352 - Identifying, processing and displaying data point clusters

4. 11411894 - Determining strength of association between user contacts

5. 11070508 - Determining an effect on dissemination of information related to an event based on a dynamic confidence level associated with the event

6. 10680991 - Determining an effect on dissemination of information related to an event based on a dynamic confidence level associated with the event

7. 10415987 - Identifying, processing and displaying data point clusters

8. 10225228 - Determining an effect on dissemination of information related to an event based on a dynamic confidence level associated with the event

9. 10091147 - Providing additional information related to a vague term in a message

10. 9875233 - Associating one or more terms in a message trail with a task entry

11. 9749274 - Associating an event attribute with a user based on a group of one or more electronic messages associated with the user

12. 9690773 - Associating one or more terms in a message trail with a task entry

13. 9569422 - Associating one or more terms in a message trail with a task entry

14. 9571427 - Determining strength of association between user contacts

15. 9552560 - Facilitating communication between event attendees based on event starting time

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1/3/2026
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