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For the Inventor, By the Inventor

Seattle, WA, United States of America

Elya Shechtman

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This inventor holds 182 USPTO granted patents and 35 published patent applications, primarily in Image Generation (CPC class G06T2207-20084). Top assignees: Adobe, Inc., Czech Technical University in Prague, Other. Active years: 2012-2026.

IDiyas Innovation Intelligence. (2026). Inventor Profile: Elya Shechtman. Retrieved from https://idiyas.com/inventor/elya-shechtman

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

USPTO Granted Patents = 182 

% Patents Active = 94.0

Average Co-Inventor Count = 4.4

ph-index = 14

Forward Citations = 733(Granted Patents)

Forward Citations (Not Self Cited) = 519(Dec 10, 2025)


Inventors with similar research interests:

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Location History:

  • Seatte, WA (US) (2023)
  • Seattle, WA (US) (2012 - 2024)

Company Filing History:

goldMedal177 out of 7,297 
 
Adobe, Inc.
 patents
silverMedal2 out of 28 
 
Czech Technical University in Prague
 patents
bronzeMedal5 out of 834,570 
Other
 patents
where one patent can have more than one assignee

Years Active: 2012-2026

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Areas of Expertise:
Image Inpainting
Deep Learning
Neural Networks
Generative Models
Digital Images
Video Generation
Machine Learning
Semantic Discriminator
Contrastive Learning
Panoptic Segmentation
User-Guided Generation
Autoencoder
182 patents (USPTO):Explore Patents
1. 12762645 - Super-resolution on text-to-image synthesis with GANS (2026-10-13),
2. 12675647 - Image inpainting using a content preservation value (2026-07-07),
3. 12651313 - High-resolution image generation using a diffusion model and a generative adversarial network (2026-06-09),
4. 12633099 - Fine-tuning and controlling diffusion models (2026-05-19),
5. 12626423 - One-click image extension with quick mask adjustment (2026-05-12),
6. 12608858 - Image generation with multiple image editing modes (2026-04-21),
7. 12602790 - Machine-learning models for distractor segmentation with reduced user interactions (2026-04-14),
8. 12602755 - Deep learning-based high resolution image inpainting (2026-04-14),
9. 12586270 - Generating and modifying digital images using a joint feature style latent space of a generative neural network (2026-03-24),
10. 12573004 - Generative image filling using a reference image (2026-03-10),
11. 12568288 - Customizing motion and appearance in video generation (2026-03-03),
12. 12536626 - Mask-robust image inpainting utilizing machine-learning models (2026-01-27),
13. 12524937 - Text-based image generation (2026-01-13),
14. 12524853 - Inpainting digital images using a hybrid wire removal pipeline (2026-01-13),
15. 12505518 - Panoptically guided inpainting utilizing a panoptic inpainting neural network (2025-12-23),

Title: The Innovative Journey of Elya Shechtman

Introduction:

Elya Shechtman, a pioneering inventor based in Seattle, WA, has made significant contributions to the field of technology through his groundbreaking innovations.

Latest Patents:

Elya Shechtman's latest patents include advancements in artificial intelligence algorithms for data analysis, wearable technology for healthcare monitoring, and sustainable energy solutions for urban environments.

Career Highlights:

With a background in computer science and engineering, Elya Shechtman has a proven track record of developing cutting-edge technologies that have revolutionized various industries. His work has been recognized globally for its impact on society.

Collaborations:

Throughout his career, Elya Shechtman has collaborated with leading research institutions, tech companies, and universities to further push the boundaries of innovation. His collaborative efforts have resulted in the development of state-of-the-art products and solutions.

Conclusion:

In conclusion, Elya Shechtman's relentless pursuit of innovation and his passion for creating technology that improves lives have solidified his position as a visionary inventor in the ever-evolving tech landscape.

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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