Jeffrey Scott Vah

This inventor holds 16 USPTO granted patents and 2 published patent applications, primarily in Artificial Intelligence. Top assignees: Dell Products Inc., Emc IP Holding Company LLC. Active years: 2020-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Jeffrey Scott Vah. Retrieved from https://idiyas.com/inventor/jeffrey-scott-vah

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

Calculating rank

USPTO Granted Patents = 16 (Patent Applications = 2)

% Patents Active = 100.0

Average Co-Inventor Count = 3.8

ph-index = 4

Forward Citations = 38(Granted Patents)

Location History:

Austin, TX (US) (2020 - 2022)
Round Rock, TX (US) (2022 - 2024)

Company Filing History:

Emc IP Holding Company LLC

patents

Years Active: 2020-2026

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Areas of Expertise:

Machine Learning

Defect Identification

Image Processing

Repair Prediction

Troubleshooting

Decentralized Network

Hierarchical Modeling

Visual Abnormalities

Zero-Shot Model

Automated Methods

Unstructured Data

Computer Repair

16 patents (USPTO):Sort by Forward CitationsExplore Patents

1. 12762686 - Machine-learning based defect identification in images of computing devices (2026-10-13),

2. 12725130 - Predicting device components for repair and/or replacement using artificial intelligence techniques (2026-09-01),

3. 12664758 - Detecting device component defects and generating corresponding recommendations using artificial intelligence techniques (2026-06-23),

4. 12587582 - Self-healing and distributed proxy deployment utilizing a decentralized network and reinforcement learning (2026-03-24),

5. 12423944 - Security-related image processing using artificial intelligence techniques (2025-09-23),

6. 12411751 - Hierarchical modeling approach for digital repair parts prediction (2025-09-09),

7. 12235884 - Facilitating reduction of noise in non-standard printed circuit board assembly component descriptions using a zero-shot model to identify salient component class descriptions (2025-02-25),

8. 12061875 - Determining indications of visual abnormalities in an unstructured data stream (2024-08-13),

9. 11989110 - Guidance system for computer repair (2024-05-21),

10. 11830105 - Service request processing utilizing modified versions of images of computing devices (2023-11-28),

11. 11487797 - Iterative application of a machine learning-based information extraction model to documents having unstructured text data (2022-11-01),

12. 11294755 - Automated method of identifying troubleshooting and system repair instructions using complementary machine learning models (2022-04-05),

13. 11275664 - Encoding and decoding troubleshooting actions with machine learning to predict repair solutions (2022-03-15),

14. 11099928 - Utilizing machine learning to predict success of troubleshooting actions for repairing assets (2021-08-24),

15. 10936809 - Method of optimized parsing unstructured and garbled texts lacking whitespaces (2021-03-02),

Title: Innovations of Jeffrey Scott Vah

Introduction

Jeffrey Scott Vah is an accomplished inventor based in Austin, TX, with a notable portfolio of 16 patents. His work primarily focuses on advancements in security-related image processing and digital repair parts prediction, showcasing his expertise in artificial intelligence and machine learning.

Latest Patents

One of his latest patents is titled "Security-related image processing using artificial intelligence techniques." This invention provides methods, apparatus, and processor-readable storage media for enhancing security through image processing. The method involves obtaining image data from user-provided components and reference components, followed by a comparison using pretrained computer vision models to perform security-related actions based on the results.

Another significant patent is the "Hierarchical modeling approach for digital repair parts prediction." This method addresses user problems with computing system components by accessing input data elements and reducing overrepresentation of class labels through a hierarchical modeling structure. The trained models generate predictions that aid in identifying the appropriate class labels for computing system components.

Career Highlights

Jeffrey has worked with prominent companies such as Dell Products Inc. and EMC IP Holding Company LLC. His experience in these organizations has contributed to his innovative approach to technology and problem-solving.

Collaborations

Throughout his career, Jeffrey has collaborated with talented individuals, including Ravi Shukla and Aaron Sanchez. These partnerships have fostered a creative environment that has led to significant advancements in their respective fields.

Conclusion

Jeffrey Scott Vah's contributions to the fields of artificial intelligence and image processing are noteworthy. His innovative patents and collaborations reflect his commitment to advancing technology and enhancing security measures.

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]

2 patents pending: