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For the Inventor, By the Inventor

Zurich, Switzerland

Daniel M Keysers

This inventor holds 49 USPTO granted patents and 8 published patent applications and 2 EPO patents, primarily in Neural Network Applications. Top assignee: Google Inc.. Active years: 2012-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Daniel M Keysers. Retrieved from https://idiyas.com/inventor/daniel-m-keysers

Data source: USPTO (United States Patent and Trademark Office) public patent records. Weekly synchronization. How IDiyas builds this profile

USPTO Granted Patents = 49 

% Patents Active = 91.8

 

Average Co-Inventor Count = 3.3

ph-index = 7

Forward Citations = 211(Granted Patents)


Location History:

  • Zurich, CH (2012)
  • Adliswil, CH (2014)
  • Stallikon, CH (2013 - 2024)

Company Filing History:

goldMedal49 out of 33,959 
 
Google Inc.
 patents

Years Active: 2012-2026

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Areas of Expertise:
Neural Networks
Video Conferencing
Automated Assistants
Transfer Learning
Generative Adversarial Models
User Interface
Deep Learning
Content Retrieval
Audio Requests
Text Recognition
Multimodal Learning
User State Information
49 patents (USPTO):Explore Patents
1. 12705703 - Processing images using mixture of experts (2026-08-11),
2. 12675687 - Training neural networks with reinitialization (2026-07-07),
3. 12626194 - Scalable transfer learning with expert models (2026-05-12),
4. 12620212 - Locked-model multimodal contrastive tuning (2026-05-05),
5. 12488237 - Training neural networks using transfer learning (2025-12-02),
6. 12468965 - Actionable suggestions for activities (2025-11-11),
7. 12379821 - Smart assist for repeated actions (2025-08-05),
8. 12362956 - Video conference content auto-retrieval and focus based on learned relevance (2025-07-15),
9. 12361696 - Multi-layer perceptron-based computer vision neural networks (2025-07-15),
10. 12192022 - Video conference content auto-retrieval and focus based on learned relevance (2025-01-07),
11. 12079954 - Modifying sensor data using generative adversarial models (2024-09-03),
12. 11956091 - Video conference content auto-retrieval and focus based on learned relevance (2024-04-09),
13. 11929072 - Using textual input and user state information to generate reply content to present in response to the textual input (2024-03-12),
14. 11887016 - Actionable suggestions for activities (2024-01-30),
15. 11860668 - Smart assist for repeated actions (2024-01-02),

Sure, here is the article about inventor Daniel M Keysers:

Title: Daniel M Keysers: Innovating Communication Technology in Zurich

Introduction: Daniel M Keysers, a prolific inventor based in Zurich, Switzerland, is known for his contributions to cutting-edge communication technologies. With a keen focus on enhancing user experiences, Keysers has made significant strides in the field of video conferencing and automated assistants.

Latest Patents: Among his 38 patents, Keysers' latest innovations include "Video conference content auto-retrieval and focus based on learned relevance" and "Using textual input and user state information to generate reply content."

Career Highlights: Currently employed at Google Inc., formerly known as Google, Keysers has played a pivotal role in shaping the tech giant's advancements in communication systems. His inventive spirit has led to the development of novel solutions that prioritize user engagement and efficiency.

Collaborations: Collaborating with talented individuals such as Thomas Deselaers and Victor Carbune, Keysers has fostered a culture of innovation and teamwork. Together, they have worked on projects that push the boundaries of traditional communication platforms.

Conclusion: In conclusion, Daniel M Keysers stands as a beacon of ingenuity in the realm of communication technology. His impressive patent portfolio and dedication to crafting seamless user interactions underscore his status as a trailblazer in the industry.

I hope you find this article insightful and informative. If you need more information or assistance, feel free to ask!

Profile summary based on public USPTO records.
Data Sources: USPTO Patent Grant XML, Patent Center, EPO & CIPO • Normalized by IDiyas Innovation Graph. Methodology & provenance architecturePlease report any incorrect information to [email protected]
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