Nir Naaman

USPTO Granted Patents = 32 (Patent Applications = 2)

CIPO Patents = 2

EPO Patents = 3 (Patent Applications = 1)

Average Co-Inventor Count = 3.9

ph-index = 6

Forward Citations = 77(Granted Patents)

Company Filing History:

31 out of 164,108

International Business Machines Corporation

Years Active: 2011-2024

where 'Filed Patents' based on already Granted Patents

32 patents (USPTO):Sort by Forward Citations

Abstract keywords

1. 11928583 - Adaptation of deep learning models to resource constrained edge devices (2024-03-12),

2. 11829888 - Modifying artificial intelligence models using model fragments (2023-11-28),

3. 11526499 - Adaptively updating databases of publish and subscribe systems using optimistic updates (2022-12-13),

4. 11381665 - Tracking client sessions in publish and subscribe systems using a shared repository (2022-07-05),

5. 10812600 - Enforcing session properties compliance for gateway connected publish-subscribe clients (2020-10-20),

6. 10812578 - Migration of durable clients in a clustered publish/subscribe system (2020-10-20),

7. 10693786 - Efficient size reduction of a bloom filter (2020-06-23),

8. 10691731 - Efficient lookup in multiple bloom filters (2020-06-23),

9. 10574619 - Cluster assisted MQTT client coverage for fat-pipe cloud applications (2020-02-25),

10. 10419163 - Adaptive network communication protocols (2019-09-17),

11. 10334067 - MQTT cluster shared subscription hub for fat-pipe cloud applications (2019-06-25),

12. 9906477 - Distributing retained messages information in a clustered publish/subscribe system (2018-02-27),

13. 9886513 - Publish-subscribe system with reduced data storage and transmission requirements (2018-02-06),

14. 9871732 - Dynamic flow control in multicast systems (2018-01-16),

15. 9673937 - Adaptive network communication protocols (2017-06-06),

Title: Innovator Spotlight: Nir Naaman

Introduction

Nir Naaman, a prominent inventor based in Haifa, Israel, has made significant contributions to the field of artificial intelligence and deep learning. With an impressive portfolio of 32 patents, Naaman's work focuses on innovative techniques that enhance the capability of deep learning models, particularly in resource-constrained environments.

Latest Patents

Among Naaman's recent innovations are two noteworthy patents:

1. **Adaptation of Deep Learning Models to Resource Constrained Edge Devices**: This patent describes techniques for generating a set of deep learning (DL) models by training an initial set using training data. It involves determining the topology of each model based on a parameters vector, generating estimate performance functions based on edge-related metrics, and producing objective functions to create a final DL model set. It culminates in receiving user selection of a DL model and deploying it to an edge device.

2. **Modifying Artificial Intelligence Models Using Model Fragments**: In this invention, an example system employs a processor to monitor system resources and performance preferences. The processor selects model fragments based on these metrics and constructs a running AI model. Additionally, it automatically modifies the model in response to changes in system resources or performance preferences, demonstrating versatility and adaptability.

Career Highlights

Nir Naaman has held pivotal roles at several innovative companies, including International Business Machines Corporation (IBM) and Globalfoundries Inc. His expertise and innovative thinking have helped shape advancements in AI technologies.

Collaborations

Naaman has collaborated with talented professionals such as Avraham Harpaz and Yoav Tock. These partnerships have been instrumental in developing cutting-edge solutions and fostering a culture of innovation within the teams he has worked with.

Conclusion

Nir Naaman's dedication to innovation in the field of artificial intelligence and deep learning is exemplified by his impressive patent portfolio and his work with leading technology companies. His contributions continue to pave the way for advancements in machine learning, making him a notable figure in the industry.

This text is generated by artificial intelligence and may not be accurate.